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Journal articles on the topic 'Inference'

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Published: 4 June 2021

Last updated: 25 July 2025

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1

Barreyro, Juan Pablo, Jazmín Cevasco, Débora Burín, and Carlos Molinari Marotto. "Working Memory Capacity and Individual Differences in the Making of Reinstatement and Elaborative Inferences." Spanish journal of psychology 15, no. 2 (2012): 471–79. http://dx.doi.org/10.5209/rev_sjop.2012.v15.n2.38857.

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This study investigated the role of working memory capacity on the making of reinstatement and causal elaborative inferences during the reading of natural texts. In order to determine participants' working memory capacity, they were asked to take the reading span task before they took part in the study. Those participants that were identified as high or low working memory capacity readers were asked to perform a lexical decision task in two conditions: pre-inference and inference. In the pre-inference condition, target words representing reinstatement or causal elaborative inferences were pres

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Wang, Yingxu. "Inference Algebra (IA)." International Journal of Cognitive Informatics and Natural Intelligence 6, no. 1 (2012): 21–47. http://dx.doi.org/10.4018/jcini.2012010102.

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Inference as the basic mechanism of thought is abilities gifted to human beings, which is a cognitive process that creates rational causations between a pair of cause and effect based on empirical arguments, formal reasoning, and/or statistical norms. It’s recognized that a coherent theory and mathematical means are needed for dealing with formal causal inferences. Presented is a novel denotational mathematical means for formal inferences known as Inference Algebra (IA) and structured as a set of algebraic operators on a set of formal causations. The taxonomy and framework of formal causal inf

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Wang, Yingxu. "Inference Algebra (IA)." International Journal of Cognitive Informatics and Natural Intelligence 5, no. 4 (2011): 61–82. http://dx.doi.org/10.4018/jcini.2011100105.

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Inference as the basic mechanism of thought is one of the gifted abilities of human beings. It is recognized that a coherent theory and mathematical means are needed for dealing with formal causal inferences. This paper presents a novel denotational mathematical means for formal inferences known as Inference Algebra (IA). IA is structured as a set of algebraic operators on a set of formal causations. The taxonomy and framework of formal causal inferences of IA are explored in three categories: a) Logical inferences on Boolean, fuzzy, and general logic causations; b) Analytic inferences on gene

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Wilhelm, Marco, and Gabriele Kern-Isberner. "Focused Inference and System P." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 7 (2021): 6522–29. http://dx.doi.org/10.1609/aaai.v35i7.16808.

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We bring in the concept of focused inference into the field of qualitative nonmonotonic reasoning by applying focused inference to System P. The idea behind drawing focused inferences is to concentrate on knowledge which seems to be relevant for answering a query while completely disregarding the remaining knowledge even at the risk of missing some meaningful information. Focused inference is motivated by mimicking snap decisions of human reasoners and aims on rapidly drawing still reasonable inferences from large sets of knowledge. In this paper, we define a series of query-dependent, syntact

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George, Marie St, Suzanne Mannes, and James E. Hoffman. "Individual Differences in Inference Generation: An ERP Analysis." Journal of Cognitive Neuroscience 9, no. 6 (1997): 776–87. http://dx.doi.org/10.1162/jocn.1997.9.6.776.

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Readers routinely draw inferences with remarkable efficiency and seemingly little cognitive effort. The present study was designed to explore different types of inferences during the course of reading, and the potential effects of differing levels of working memory capacity on the likelihood that inferences would be made. The electroencephalogram (EEG) was recorded from five scalp sites while participants read 90 paragraphs, composed of 60 experimental paragraphs and 30 filler paragraphs. Each experimental paragraph was four sentences long, and the final sentence stated explicitly the inferenc

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Murza, Kimberly A., Chad Nye, Jamie B. Schwartz, Barbara J. Ehren, and Debbie L. Hahs-Vaughn. "A Randomized Controlled Trial of an Inference Generation Strategy Intervention for Adults With High-Functioning Autism Spectrum Disorder." American Journal of Speech-Language Pathology 23, no. 3 (2014): 461–73. http://dx.doi.org/10.1044/2014_ajslp-13-0012.

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PurposeThe present intervention study investigated the efficacy of the ACT & Check Strategy intervention to improve inference generation when reading, metacognitive ability, general reading comprehension, and social inference ability in adults with high-functioning autism spectrum disorder (HF-ASD).MethodTwenty-five adults with HF-ASD were randomly assigned to either a treatment or a control group. Treatment sessions were conducted in 1-hr sessions, twice a week, for a total of 6 weeks. Treatment focused on explicit instruction of components of inference generation, categories of inference

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Starns, Jeffrey J., Andrea M. Cataldo, Caren M. Rotello, et al. "Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis." Advances in Methods and Practices in Psychological Science 2, no. 4 (2019): 335–49. http://dx.doi.org/10.1177/2515245919869583.

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Scientific advances across a range of disciplines hinge on the ability to make inferences about unobservable theoretical entities on the basis of empirical data patterns. Accurate inferences rely on both discovering valid, replicable data patterns and accurately interpreting those patterns in terms of their implications for theoretical constructs. The replication crisis in science has led to widespread efforts to improve the reliability of research findings, but comparatively little attention has been devoted to the validity of inferences based on those findings. Using an example from cognitiv

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Krishna Raju, Rama. "Dynamic Memory Inference Network for Natural Language Inference (2017)." International Journal of Science and Research (IJSR) 6, no. 2 (2017): 2219–30. http://dx.doi.org/10.21275/sr24926091431.

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9

Bahri, Toufik, and Abdulqader A. Al Hussain. "Question Type and Order of Inference in Inferential Processes during Reading Comprehension." Perceptual and Motor Skills 85, no. 2 (1997): 655–64. http://dx.doi.org/10.2466/pms.1997.85.2.655.

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For three groups of 20 subjects each who participated reading time was examined when stories suggested goal and state inferences which could be made by readers when asked state questions, goal questions, or no questions at all. Order of inference statement was also used as a variable. In addition, inferable statements were either left in or out of the text. Subjects read an equal number (12) of stories. Analysis showed that state inference took longer time than goal inference. Also, it took longer for subjects to draw inferences when the inferrable statement was absent than when it was present

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10

Bar-Haim, Roy, Ido Dagan, and Jonathan Berant. "Knowledge-Based Textual Inference via Parse-Tree Transformations." Journal of Artificial Intelligence Research 54 (September 9, 2015): 1–57. http://dx.doi.org/10.1613/jair.4584.

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Textual inference is an important component in many applications for understanding natural language. Classical approaches to textual inference rely on logical representations for meaning, which may be regarded as "external" to the natural language itself. However, practical applications usually adopt shallower lexical or lexical-syntactic representations, which correspond closely to language structure. In many cases, such approaches lack a principled meaning representation and inference framework. We describe an inference formalism that operates directly on language-based structures, particula

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11

Fu, Xiyan, and Anette Frank. "Exploring Continual Learning of Compositional Generalization in NLI." Transactions of the Association for Computational Linguistics 12 (2024): 912–32. http://dx.doi.org/10.1162/tacl_a_00680.

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Abstract Compositional Natural Language Inference (NLI) has been explored to assess the true abilities of neural models to perform NLI. Yet, current evaluations assume models to have full access to all primitive inferences in advance, in contrast to humans that continuously acquire inference knowledge. In this paper, we introduce the Continual Compositional Generalization in Inference (C2Gen NLI) challenge, where a model continuously acquires knowledge of constituting primitive inference tasks as a basis for compositional inferences. We explore how continual learning affects compositional gene

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Landis, Christopher B., and Joshua A. Kroll. "Mitigating Inference Risks with the NIST Privacy Framework." Proceedings on Privacy Enhancing Technologies 2024, no. 1 (2024): 217–31. http://dx.doi.org/10.56553/popets-2024-0013.

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The NIST Privacy Framework describes itself as a comprehensive approach to organization-wide privacy program management. However, inferences can yield sensitive information of identities or attributes from nonsensitive information. Privacy governance must protect this information. Although many people and organizations are expanding their privacy definitions to include inferences, our gap analysis reveals that the framework's mapped controls are insufficient for managing inference-driven risk. The framework does not attend organizational focus to privacy inference risk sufficiently to support

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Simanullang, Lestari Tasya Lidya, Erwin Ashari, Juwita Boneka Sinaga, and Warno Edi. "Inferential questions in English textbook: A case study." Celtic : A Journal of Culture, English Language Teaching, Literature and Linguistics 12, no. 1 (2025): 13–24. https://doi.org/10.22219/celtic.v12i1.39715.

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This research focuses on inference analysis in English textbooks used by Indonesia students. This study aims to discover and describe the inference patterns found in textbooks. The method used in this study is descriptive qualitative. The data sources come from English books, such as English For Nusantara and Bright: An English Course. Ten data are used in the book, five labeled as Code A from English For Nusantara and five labeled as Code B from Bright An English. The data were analyzed interpretatively through inference-type theory. The analysis includes ten types of inferences: cohesive inf

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De Cooman, Gert, Jasper De Bock, and Márcio Alves Diniz. "Coherent Predictive Inference under Exchangeability with Imprecise Probabilities." Journal of Artificial Intelligence Research 52 (January 10, 2015): 1–95. http://dx.doi.org/10.1613/jair.4490.

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Coherent reasoning under uncertainty can be represented in a very general manner by coherent sets of desirable gambles. In a context that does not allow for indecision, this leads to an approach that is mathematically equivalent to working with coherent conditional probabilities. If we do allow for indecision, this leads to a more general foundation for coherent (imprecise-)probabilistic inference. In this framework, and for a given finite category set, coherent predictive inference under exchangeability can be represented using Bernstein coherent cones of multivariate polynomials on the simpl

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Morgan, Mary S. "Narrative Inference with and without Statistics." History of Political Economy 53, no. 6 (2021): 113–38. http://dx.doi.org/10.1215/00182702-9414803.

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This article investigates the role played by narrative in drawing inferences from statistics before the adoption of formal inference regimes in economics. Two well-known, and exemplary, cases of informal inference provide the materials. Nikolai Kondratiev’s struggles to make inferences about the existence of his “long waves” from heaps of statistics in the 1920s contrast sharply with Thomas Robert Malthus’s confident account of demographic-economic oscillations made on the basis of the limited numbers available in the late eighteenth century. Comparison of their inferential reasoning, using de

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Lehman-Blake, Margaret T., and Connie A. Tompkins. "Predictive Inferencing in Adults With Right Hemisphere Brain Damage." Journal of Speech, Language, and Hearing Research 44, no. 3 (2001): 639–54. http://dx.doi.org/10.1044/1092-4388(2001/052).

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Predictive inferencing was evaluated in 13 adults with right hemisphere damage (RHD) and 11 adults without brain damage (NBD). Brief narrative stimuli that strongly suggested a single outcome were constructed to vary recency of mention of inference-related information. Reading times were recorded for narrative-final sentences that disconfirmed the target inferences. Slowed reading time on the final sentences was an indicator of inference generation. Adults with RHD generated target predictive inferences in contexts with recent mention of strongly biasing inference-related information. This gro

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Kim, Woori, Mikyung Shin, and Yongseok Yoo. "Comparative Analysis of Inferencing in Low-Reading and Average-Reading Comprehenders: Utilizing the Think-Aloud Protocol." Communication Sciences & Disorders 28, no. 3 (2023): 480–91. http://dx.doi.org/10.12963/csd.23976.

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Objectives: This is a conceptual replication aiming to investigate the cognitive processes of students with reading comprehension difficulties using the think-aloud protocol. Methods: Among 72 third- and fourth-grade participants, 28 poor comprehenders and 44 average students were identified based on screening criteria and standardized tests. The think-aloud protocol was used to monitor comprehension processes during reading. The participants verbalized their thoughts as they read expository and narrative texts. Those responses were transcribed and coded according to inference rates, correctne

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18

Alhaqbani, Bandar, and Colin Fidge. "Probabilistic Inference Channel Detection and Restriction Applied to Patients’ Privacy Assurance." International Journal of Information Security and Privacy 4, no. 4 (2010): 35–59. http://dx.doi.org/10.4018/jisp.2010100103.

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Traditional access control models protect sensitive data from unauthorised direct accesses; however, they fail to prevent indirect inferences. Information disclosure via inference channels occurs when secret information is derived from unclassified (non-secure) information and other sources like metadata and public observations. Previously, techniques using precise and fuzzy functional dependencies were proposed to detect inference channels. However, such methods are inappropriate when probabilistic relationships exist among data items that may be used to infer information with a predictable l

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Din, Muhammad, and Mamuna Ghani. "Evaluating University Students’ Inference Making Ability: A Study at Bachelor Level in Pakistan." International Journal of English Linguistics 9, no. 5 (2019): 351. http://dx.doi.org/10.5539/ijel.v9n5p351.

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Inference means the process of deriving a conclusion from a set of premises, including a conclusion that is probably in relation to the premises. This study has aimed to evaluate university students&rsquo; inference making ability. To explore this aim, the present study has set five research objectives which include to understand university students&rsquo; attitude towards critical thinking subset of making inferences, find out the relationship between university students&rsquo; attitude towards making inferences and their ability in making inferences, know whether critical thinkin

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20

Gras, Doriane, Hubert Tardieu, and Serge Nicolas. "Predictive Inference Activation." Swiss Journal of Psychology 71, no. 3 (2012): 141–48. http://dx.doi.org/10.1024/1421-0185/a000081.

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Predictive inferences are anticipations of what could happen next in the text we are reading. These inferences seem to be activated during reading, but a delay is necessary for their construction. To determine the length of this delay, we first used a classical word-naming task. In the second experiment, we used a Stroop-like task to verify that inference activation was not due to strategies applied during the naming task. The results show that predictive inferences are naturally activated during text reading, after approximately 1 s.

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Liptáková, Ľudmila. "On the research of children’s text comprehension." Journal of Linguistics/Jazykovedný casopis 74, no. 2 (2023): 577–92. http://dx.doi.org/10.2478/jazcas-2024-0012.

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Abstract The paper presents theoretical background and empirical research on text comprehension processes of a junior school-age child. The first part of the paper discusses the most influential models of text comprehension and inference making as centrally important component of comprehension. The research findings concerning children’s text comprehension are discussed as well. Further, we present our ongoing empirical research, which focuses on children’s inference making when listening to and reading an informational, narrative, and multimodal text. We focus both on the online and offline i

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Waking, Douglas A., and Christy L. Kluttz. "Effects of Task on the Activation of Predictive Inferences." Psychological Reports 83, no. 3_suppl (1998): 1287–96. http://dx.doi.org/10.2466/pr0.1998.83.3f.1287.

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Research on the activation of predictive inferences has provided inconsistent results that may be explained within a contextual view of reading. The present study tested whether the type of test for explicit memory would affect the activation of knowledge-based predictive inferences. The information necessary for the activation of a predictive inference was provided to readers in four different conditions (no inference, local processing, global processing, coherence). Manipulation was accomplished by varying the type of question asked after reading the passage (verbatim, factual, or inference)

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León, Jose A., María T. Dávalos, Inmaculada Escudero, Ricardo Olmos, Yurena Morera, and Manuel Froufe. "Procesamiento de inferencias emocionales. Un análisis sobre el efecto de la valencia y la dirección causal mediante una tarea de decisión léxica." Anales de Psicología 31, no. 2 (2015): 677. http://dx.doi.org/10.6018/analesps.31.2.167391.

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In two experiments we investigated the role that activation of emotional inferences when readers represent fictional characters' emotional states using an affective lexical decision task. Subjects read short stories that described concrete actions. In the first experiment, we analyzed whether the valence (positive or negative) was an important factor of inference´s activation. The results showed that valence was determinant factor in the moment that emotional inference was generated, being the positive valence faster than negative. In the second experiment we studied whether the emotion infere

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Li, Zhongbin, Kun Yue, Lixing Yu, and Jiahui Wang. "An Inference Framework of Markov Logic Network for Link Prediction in Heterogeneous Networks." Applied Sciences 15, no. 8 (2025): 4424. https://doi.org/10.3390/app15084424.

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The presence of multiplex edges and sparse links often hampers the efficacy of link prediction (LP) tasks. By harnessing the expressive power of Markov logic network (MLN) formulations, multiplex edges can be unified to enhance LP effectiveness. However, scaling up inferences for effective LP remains challenging due to the inefficiency of traditional MLN inference methods. To tackle this issue, we redefine LP tasks within heterogeneous networks using MLN inferences and introduce a tailored inference framework to handle unobserved nodes and complex MLN structures. We propose a method to partiti

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Chen, Dingding, Yanchen Deng, Ziyu Chen, Wenxing Zhang, and Zhongshi He. "HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-Based Inference." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (2020): 7087–94. http://dx.doi.org/10.1609/aaai.v34i05.6195.

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Search and inference are two main strategies for optimally solving Distributed Constraint Optimization Problems (DCOPs). Recently, several algorithms were proposed to combine their advantages. Unfortunately, such algorithms only use an approximated inference as a one-shot preprocessing phase to construct the initial lower bounds which lead to inefficient pruning under the limited memory budget. On the other hand, iterative inference algorithms (e.g., MB-DPOP) perform a context-based complete inference for all possible contexts but suffer from tremendous traffic overheads. In this paper, (i) hy

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Yoo, Yongseok. "On the Dynamics of Inferential Behavior while Reading Expository and Narrative Texts." Brain Sciences 14, no. 5 (2024): 428. http://dx.doi.org/10.3390/brainsci14050428.

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Inference plays a key role in reading comprehension. This study examines changes in inferential behavior while reading different genres. The inferential behavior of 28 students with reading disabilities (RDs) and 44 students without RDs was quantified while they read expository and narrative texts. First, the average rates of inference attempts and correct inferences were measured during reading. Then, the same rates were measured separately during early and late reading to see if there was a change in inferential behavior. The results show that the change in inferential behavior depends on th

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Bill, Cory, Elena Pagliarini, Jacopo Romoli, Lyn Tieu, and Stephen Crain. "Children’s Interpretation of Sentences Containing Multiple Scalar Terms." Journal of Semantics 38, no. 4 (2021): 601–37. http://dx.doi.org/10.1093/jos/ffab016.

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Abstract Sentences containing the scalar term “some”, such as “The pig carried some of his rocks”, are usually interpreted as conveying the scalar inference that the pig did not carry all of his rocks. Previous research has reported that when interpreting such sentences, children tend to derive fewer of these scalar inferences than adults ( Noveck (2001); Papafragou & Musolino (2003); Guasti et al. (2005), among others). One approach to explaining these results contends that children have difficulties accessing the alternative sentences involved in the derivation of such scalar inferences.

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Zhang, Sheng, Rachel Rudinger, Kevin Duh, and Benjamin Van Durme. "Ordinal Common-sense Inference." Transactions of the Association for Computational Linguistics 5 (December 2017): 379–95. http://dx.doi.org/10.1162/tacl_a_00068.

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Humans have the capacity to draw common-sense inferences from natural language: various things that are likely but not certain to hold based on established discourse, and are rarely stated explicitly. We propose an evaluation of automated common-sense inference based on an extension of recognizing textual entailment: predicting ordinal human responses on the subjective likelihood of an inference holding in a given context. We describe a framework for extracting common-sense knowledge from corpora, which is then used to construct a dataset for this ordinal entailment task. We train a neural seq

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Molinari Marotto, Carlos, Juan Pablo Barreyro, Jazmín Cevasco, and Paul Van den Broek. "Generation of Emotional Inferences during Text Comprehension: Behavioral Data and Implementation through the Landscape Model." Escritos de Psicología - Psychological Writings 4, no. 1 (2011): 9–17. http://dx.doi.org/10.24310/espsiescpsi.v4i1.13308.

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This study investigated the generation of emotional inferences during the reading and recall of narrative texts. Experiment 1 compared the fit of two simulations of text comprehension to the recall data. One simulation examined causal and referential inferences, while the other examined causal, referential and emotional inferences. We found that the simulation that involved emotional inferences provided a better fit to the human data than the other simulation. Experiment 2 tested whether emotional inferences are generated online by recording lexical decision times at preinference and inference

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HAMAMI, YACIN. "MATHEMATICAL INFERENCE AND LOGICAL INFERENCE." Review of Symbolic Logic 11, no. 4 (2018): 665–704. http://dx.doi.org/10.1017/s1755020317000326.

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AbstractThe deviation of mathematical proof—proof in mathematical practice—from the ideal of formal proof—proof in formal logic—has led many philosophers of mathematics to reconsider the commonly accepted view according to which the notion of formal proof provides an accurate descriptive account of mathematical proof. This, in turn, has motivated a search for alternative accounts of mathematical proof purporting to be more faithful to the reality of mathematical practice. Yet, in order to develop and evaluate such alternative accounts, it appears as a necessary prerequisite to first possess a

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Then, Jenisha, Ferry Jaya Permana, and Benny Yong. "PARAMETER ESTIMATION OF LOGNORMAL AND PARETO TYPE I DISTRIBUTIONS USING FREQUENTIST AND BAYESIAN INFERENCES." BAREKENG: Jurnal Ilmu Matematika dan Terapan 19, no. 1 (2025): 141–52. https://doi.org/10.30598/barekengvol19iss1pp141-152.

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Extreme events are events that rarely occur but they cause substantial losses. Insurance companies need to take extreme events into account in risk management because extreme events can have a negative impact on the company's financial health. As a result, insurance companies need an appropriate loss model that matches the empirical data from these extreme events. A distribution that is heavy-tailed and skewed to the right is a good distribution for modeling the magnitude of losses from extreme events. In this paper, two distributions with heavy tails and skew to the right will be used to mode

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Markovits, Henry, Cécile Saelen, and Hugues Lortie Forgues. "An Inverse Belief–Bias Effect." Experimental Psychology 56, no. 2 (2009): 112–20. http://dx.doi.org/10.1027/1618-3169.56.2.112.

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Two studies examined the hypothesis that accepting false premises as true in order to make the modus ponens (MP) inference requires inhibition of contradictory knowledge. Study 1 presented both MP and affirmation of the consequent (AC) inferences using either false, but plausible premises or completely unbelievable premises, with standard logical constructions using either an evaluation or a production paradigm. The rate of acceptance of the MP inferences was significantly greater with unbelievable premises than with plausible premises, in both evaluation and production, while no such effect w

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Kane, Benjamin, Will Gantt, and Aaron Steven White. "Intensional Gaps: Relating veridicality, factivity, doxasticity, bouleticity, and neg-raising." Semantics and Linguistic Theory 31 (January 5, 2022): 570. http://dx.doi.org/10.3765/salt.v31i0.5137.

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We investigate which patterns of lexically triggered doxastic, bouletic, neg(ation)-raising, and veridicality inferences are (un)attested across clause-embedding verbs in English. To carry out this investigation, we use a multiview mixed effects mixture model to discover the inference patterns captured in three lexicon-scale inference judgment datasets: two existing datasets, MegaVeridicality and MegaNegRaising, which capture veridicality and neg-raising inferences across a wide swath of the English clause-embedding lexicon, and a new dataset, MegaIntensionality, which similarly captures doxas

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Bowles, C. Travis, Arthur D. Fisk, and Wendy A. Rogers. "Inference and the Use of Similes and Metaphors in Warnings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 19 (2002): 1703–7. http://dx.doi.org/10.1177/154193120204601903.

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Warning content must be written to assure that the user knows how to apply the information at the appropriate time. Since the warning cannot provide information about all possible circumstances, in some situations individuals must make inferences about safe behavior. This paper contains two experiments that investigated compliance with warning information in situations that do and situations that do not require inferences. The first experiment, with 39 undergraduate students, tested simile use in warnings to improve compliance in inference situations. The second experiment, with 44 undergradua

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Luo, Yu, and Jiaying Zhao. "Statistical Learning Creates Novel Object Associations via Transitive Relations." Psychological Science 29, no. 8 (2018): 1207–20. http://dx.doi.org/10.1177/0956797618762400.

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A remarkable ability of the cognitive system is to make novel inferences on the basis of prior experiences. What mechanism supports such inferences? We propose that statistical learning is a process through which transitive inferences of new associations are made between objects that have never been directly associated. After viewing a continuous sequence containing two base pairs (e.g., A–B, B–C), participants automatically inferred a transitive pair (e.g., A–C) where the two objects had never co-occurred before (Experiment 1). This transitive inference occurred in the absence of explicit awa

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Johar, Gita Venkataramani, Jaideep Sengupta, and Jennifer L. Aaker. "Two Roads to Updating Brand Personality Impressions: Trait versus Evaluative Inferencing." Journal of Marketing Research 42, no. 4 (2005): 458–69. http://dx.doi.org/10.1509/jmkr.2005.42.4.458.

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This research examines the dynamic process of inference updating. The authors present a framework that delineates two mechanisms that guide the updating of personality trait inferences about brands. The results of three experiments show that chronics (those for whom the trait is accessible) update their initial inferences on the basis of the trait implications of new information. Notably, nonchronics (those for whom the trait is not accessible) also update their initial inferences, but they do so on the basis of the evaluative implications of new information. The framework adds to the inferenc

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Romoli, Jacopo, and Agata Renans. "Multiplicity and Modifiers." Journal of Semantics 37, no. 3 (2020): 455–74. http://dx.doi.org/10.1093/jos/ffaa005.

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Abstract A sentence with an adverbial modifier under negation like Mike didn’t wash the window with soap gives rise to an inference that Mike did wash the window. A sentence with a plural noun like Mike washed windows gives rise to a so-called ‘multiplicity’ inference that Mike washed multiple windows. In this note, we focus on the interaction between these two inferences in sentences containing both an adverbial modifier and a plural noun under negation, like Mike didn’t wash windows with soap. We observe that this sentence has a reading conveying that Mike didn’t wash any window with soap bu

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Vázquez-Polo, Francisco-José, Miguel-Ángel Negrín-Hernández, and María Martel-Escobar. "Meta-Analysis with Few Studies and Binary Data: A Bayesian Model Averaging Approach." Mathematics 8, no. 12 (2020): 2159. http://dx.doi.org/10.3390/math8122159.

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In meta-analysis, the existence of between-sample heterogeneity introduces model uncertainty, which must be incorporated into the inference. We argue that an alternative way to measure this heterogeneity is by clustering the samples and then determining the posterior probability of the cluster models. The meta-inference is obtained as a mixture of all the meta-inferences for the cluster models, where the mixing distribution is the posterior model probabilities. When there are few studies, the number of cluster configurations is manageable, and the meta-inferences can be drawn with BMA techniqu

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Franks, Bridget A. "Deductive Reasoning with Prose Passages: Effects of Age, Inference Form, Prior Knowledge, and Reading Skill." International Journal of Behavioral Development 21, no. 3 (1997): 501–35. http://dx.doi.org/10.1080/016502597384767.

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This study applied knowledge about inference-making from the deductive reasoning literature to the drawing of specific inferences from prose passages. It explored the effects of age, inference form, prior knowledge, and reading skill on inferential comprehension. In Experiment 1, fourth-grade, seventh-grade, and college students read three prose passages, each containing six inferential questions based on premises expressed in the passages. Premise information was either true, false, or neutral with regard to subjects’ prior knowledge. To answer the questions correctly, subjects were required

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Goodwin, Chris, and Enrique Ortiz. "It's a Girl! Random Numbers, Simulations, and the Law of Large Numbers." Mathematics Teaching in the Middle School 20, no. 9 (2015): 561–64. http://dx.doi.org/10.5951/mathteacmiddscho.20.9.0561.

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Modeling using mathematics and making inferences about mathematical situations are becoming more and more prevalent in most fields of study. When we want to generalize about a population or make predictions of what could occur, we cannot use descriptive statistics. Instead, we turn to inference. Simulation and sampling are essential in building a foundation for statistical inference.

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Wang, Yingxu. "Formal Rules for Fuzzy Causal Analyses and Fuzzy Inferences." International Journal of Software Science and Computational Intelligence 4, no. 4 (2012): 70–86. http://dx.doi.org/10.4018/jssci.2012100105.

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Causal inference is one of the central capabilities of the natural intelligence that plays a crucial role in thinking, perception, and problem solving. Fuzzy inferences are an extended form of formal inferences that provide a denotational mathematical means for rigorously dealing with degrees of matters, uncertainties, and vague semantics of linguistic variables, as well as for rational reasoning the semantics of fuzzy causalities. This paper presents a set of formal rules for causal analyses and fuzzy inferences such as those of deductive, inductive, abductive, and analogical inferences. Rule

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Chernev, Alexander, and Gregory S. Carpenter. "The Role of Market Efficiency Intuitions in Consumer Choice: A Case of Compensatory Inferences." Journal of Marketing Research 38, no. 3 (2001): 349–61. http://dx.doi.org/10.1509/jmkr.38.3.349.18865.

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The authors examine consumer inferences about product attributes that are unobservable at the time of the decision. Extant research predicts that in the absence of an explicit correlation between product attributes, consumers will infer that the brand that is superior on the observable attributes is also superior on the unobservable attributes. The authors propose an alternative inference strategy that makes the counterintuitive prediction that the apparently superior brand is inferior on the unobservable attributes. The authors refer to these inferences as “compensatory inferences” and assert

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Akagi, Yasunori, Takuya Nishimura, Yusuke Tanaka, Takeshi Kurashima, and Hiroyuki Toda. "Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (2020): 3163–70. http://dx.doi.org/10.1609/aaai.v34i04.5713.

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Collective Flow Diffusion Model (CFDM) is a general framework to find the hidden movements underlying aggregated population data. The key procedure in CFDM analysis is MAP inference of hidden variables. Unfortunately, existing approaches fail to offer exact MAP inferences, only approximate versions, and take a lot of computation time when applied to large scale problems. In this paper, we propose an exact and efficient method for MAP inference in CFDM. Our key idea is formulating the MAP inference problem as a combinatorial optimization problem called Minimum Convex Cost Flow Problem (C-MCFP)

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Ramsey, Charles A. "Considerations for Inference to Decision Units." Journal of AOAC INTERNATIONAL 98, no. 2 (2015): 288–94. http://dx.doi.org/10.5740/jaoacint.14-292.

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Abstract The goal of sampling is to take a small portion of a target material for analysis instead of collecting all the material. If sampling is done following certain principles, then inference can be made from analytical results of the portion taken back to the entire target material (Decision Unit). There are different sampling strategies that are dependent on theproperties of the material being sampled as well as different methods for making inferences from analytical results to the Decision Unit (DU). A thorough understanding of material properties and methods for inference is therefore

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Charles, Cara, Ra’Shida Rockette, and Caitlin Bowman. "MEMORY CHANGES IN COGNITIVELY HEALTHY OLDER ADULTS: AGE EFFECTS IN MEMORY-BASED INFERENCE." Innovation in Aging 8, Supplement_1 (2024): 690–91. https://doi.org/10.1093/geroni/igae098.2257.

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Abstract Memory changes in older age are well documented, even among cognitively healthy older adults. Most prior research has focused on age-related declines in remembering details of individual experiences. However, memory-based inference is another important memory ability that allows us to make connections across separate experiences to make novel decisions. Little is known about the extent of age differences in inference abilities. In the present experiment, we administered an inference task to young and cognitively healthy older adults that asked them to both remember pairs of items that

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Nishiyama, Yu, Motonobu Kanagawa, Arthur Gretton, and Kenji Fukumizu. "Model-based kernel sum rule: kernel Bayesian inference with probabilistic models." Machine Learning 109, no. 5 (2020): 939–72. http://dx.doi.org/10.1007/s10994-019-05852-9.

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AbstractKernel Bayesian inference is a principled approach to nonparametric inference in probabilistic graphical models, where probabilistic relationships between variables are learned from data in a nonparametric manner. Various algorithms of kernel Bayesian inference have been developed by combining kernelized basic probabilistic operations such as the kernel sum rule and kernel Bayes’ rule. However, the current framework is fully nonparametric, and it does not allow a user to flexibly combine nonparametric and model-based inferences. This is inefficient when there are good probabilistic mod

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Al-Sulaimaan, Misbah M. D., and Teeba N. T. Al-Khaffaf. "Rationality and Gricean Inference with Reference to English-Arabic Translation." International Journal of Social Sciences & Humanities (IJSSH) 1, no. 1 (2016): 138–76. http://dx.doi.org/10.58885/ijssh.v1i1.138.ma.

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The present study tackles “Rationality and Gricean inference” in English and its translation from English into Arabic. Inference can be defined as a logical conclusion that is drawn from a premise and it is used to describe that process which the reader (hearer) must go through to get from the literal meaning of what is written (or said) to what the writer (speaker) intended to convey. Rationality can be defined as thinking, speaking, reasoning, making a decision, or acting in a way that is generally reliable and efficient for achieving one's goals. This study aims at (1) specifying and studyi

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Liu, Yu, Anurag Andhare, and Kyoung-Don Kang. "Corun: Concurrent Inference and Continuous Training at the Edge for Cost-Efficient AI-Based Mobile Image Sensing." Sensors 24, no. 16 (2024): 5262. http://dx.doi.org/10.3390/s24165262.

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Intelligent mobile image sensing powered by deep learning analyzes images captured by cameras from mobile devices, such as smartphones or smartwatches. It supports numerous mobile applications, such as image classification, face recognition, and camera scene detection. Unfortunately, mobile devices often lack the resources necessary for deep learning, leading to increased inference latency and rapid battery consumption. Moreover, the inference accuracy may decline over time due to potential data drift. To address these issues, we introduce a new cost-efficient framework, called Corun, designed

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Michalewicz, Zbigniew, and Anthony Yeo. "Multiranges and Multitrackers in Statistical Databases." Fundamenta Informaticae 11, no. 1 (1988): 41–48. http://dx.doi.org/10.3233/fi-1988-11104.

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The goal of statistical databases is to provide statistics about groups of individuals while protecting their privacy. Sometimes. by correlating enough statistics, sensitive data about individual can be inferred. The problem of protecting against such indirect disclosures of confidential data is called the inference problem and a protecting mechanism – an inference control. A good inference control mechanism should be effective (it should provide security to a reasonable extent) and feasible (a practical way exists to enforce it). At the same time it should retain the richness of the informati

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Melgarejo, Teófilo Félix Valentín, Pablo Lenin La Madrid Vivar, Clodoaldo Ramos Pando, Pablo Lolo Valentín Melgarejo, and Agustín Arturo Aguirre Adauto. "Inference and reading comprehension in university students." Nurture 18, no. 4 (2024): 785–94. http://dx.doi.org/10.55951/nurture.v18i4.846.

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Purpose: The objective of this research was to determine the relationship between inference and reading comprehension. We sought to verify the relationship between inductive and deductive inferences in the comprehensive reading of Daniel Alcides Carrión National University Peru students majoring in communication and literature. Design/Methodology/Approach: The correlational-explanatory research design was used since the correlation of the study variables was sought through scientific and specifically analytical, deductive and interpretive methodology on a population of 104 and the probabilisti

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