Relevant bibliographies by topics / Inference reading

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Inference reading'

Author: Grafiati
Published: 4 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Inference reading"

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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 (August 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 inferences, and increasingly independent strategy use.ResultsThe treatment group demonstrated significantly superior performance on 1 of 2 measures of inference generation in reading and 1 measure of metacognitive ability compared with the control group. Significant differences between groups were not found on measures of reading comprehension or social inference ability.ConclusionThese findings suggest that the ACT & Check Strategy was effective in improving participants' ability to generate inferences in reading and certain metacognitive abilities, but the skills do not appear to generalize to other social communication contexts, such as social inference generation. This research provides a measure of support for explicitly teaching inference generation to address a reading inference deficit in adults with HF-ASD.
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Gras, Doriane, Hubert Tardieu, and Serge Nicolas. "Predictive Inference Activation." Swiss Journal of Psychology 71, no. 3 (January 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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McKoon, Gail, and Roger Ratcliff. "Inference during reading." Psychological Review 99, no. 3 (1992): 440–66. http://dx.doi.org/10.1037/0033-295x.99.3.440.

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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 (July 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 presented immediately before the sentences that were predicted to prompt them. In the inference condition, the target words were presented immediately after the sentences that were predicted to prompt the inferences. Results indicated that, for the high working memory capacity readers, lexical decision times were faster at the inference compared to the pre-inference locations for both types of inferences. In the case of low working capacity readers, lexical decision times were faster at the inference compared to the pre-inference locations only for reinstatement inferences. These findings suggest that working memory capacity plays a role in the making of causal inferences during the comprehension of natural texts.
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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 (November 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 inference that readers did or did not make. There were four types of experimental paragraphs: (1) Bridging inference, (2) Elaborative inference, (3) Word-Based Priming control, and (4) No Inference control. Participants were tested using the Daneman and Carpenter (1980) Reading Span Task and categorized as having low or high working memory capacity. The average peaks of the N400 component of the event-related brain potential (EM) were used as a measure of semantic priming and integration, such that the lower the N400 was in response to the explicitly stated inference concept, the more likely it was that the reader made the inference. Results indicate that readers with high working memory capacity made both bridging (necessary) and elaborative (optional) inferences during reading, whereas readers with low working memory capacity made only bridging inferences during reading. We interpret the findings within the framework of the Capacity Constrained Comprehension model of Just and Carpenter (1992).
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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 (October 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 in the text. The effect of inference type, and condition on reading comprehension is discussed.
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Warnidah, Nining, Bambang Suwarno, and Arono . "STUDENTS’ DIFFICULTIES IN MAKING INFERENCE IN READING NARRATIVE PASSAGES AT THE SOCIAL ELEVENT GRADE OF SMAN 1 CURUP." JOALL (Journal of Applied Linguistics & Literature) 1, no. 2 (March 11, 2018): 78–94. http://dx.doi.org/10.33369/joall.v1i2.4206.

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This study aimed to find out the students’ difficulties in making inference in reading narrative passages in making inference in reading narrative passages. The population of this study included the eleventh graders of SMAN 1 Curup, and the students of XI SOS 4, which consisted of 34 students, became the research sample. For the instrument, the researcher used reading test which consisted of 40 questions and questionnaire which consisted of 30 items. The result showed that the students’ overall difficulty in making inference in reading narrative passages belonged to “moderate” category. It was proved by the students’ reading error mean score which was 47.5. The students’ highest difficulty was on inferences about the author’s attitude (5.88%, or “very high”).
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O'Brien, Edward J., Susan A. Duffy, and Jerome L. Myers. "Anaphoric inference during reading." Journal of Experimental Psychology: Learning, Memory, and Cognition 12, no. 3 (1986): 346–52. http://dx.doi.org/10.1037/0278-7393.12.3.346.

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Hall, Colby, and Marcia A. Barnes. "Inference Instruction to Support Reading Comprehension for Elementary Students With Learning Disabilities." Intervention in School and Clinic 52, no. 5 (December 5, 2016): 279–86. http://dx.doi.org/10.1177/1053451216676799.

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Making inferences during reading is a critical standards-based skill and is important for reading comprehension. This article supports the improvement of reading comprehension for students with learning disabilities (LD) in upper elementary grades by reviewing what is currently known about inference instruction for students with LD and providing detailed suggestions and a five-step process for teaching students to make text-connecting and knowledge-based inferences while reading. By bolstering this key reading comprehension skill in the upper elementary grades, teachers can better prepare students for the increased reading comprehension demands of middle school.
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Joseph, Holly, Elizabeth Wonnacott, and Kate Nation. "Online inference making and comprehension monitoring in children during reading: Evidence from eye movements." Quarterly Journal of Experimental Psychology 74, no. 7 (March 15, 2021): 1202–24. http://dx.doi.org/10.1177/1747021821999007.

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Inference generation and comprehension monitoring are essential elements of successful reading comprehension. While both improve with age and reading development, little is known about when and how children make inferences and monitor their comprehension during the reading process itself. Over two experiments, we monitored the eye movements of two groups of children (age 8–13 years) as they read short passages and answered questions that tapped local (Experiment 1) and global (Experiment 2) inferences. To tap comprehension monitoring, the passages contained target words which were consistent or inconsistent with the context. Comprehension question location was also manipulated with the question appearing before or after the passage. Children made local inferences during reading, but the evidence was less clear for global inferences. Children were sensitive to inconsistencies that relied on the generation of an inference, consistent with successful comprehension monitoring, although this was seen only very late in the eye movement record. Although question location had a large effect on reading times, it had no effect on global comprehension in one experiment and reading the question first had a detrimental effect in the other. We conclude that children appear to prioritise efficiency over completeness when reading, generating inferences spontaneously only when they are necessary for establishing a coherent representation of the text.
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Dissertations / Theses on the topic "Inference reading"

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Clarke, Leesa. "Inference generation and reading disability." Thesis, University of York, 2009. http://etheses.whiterose.ac.uk/846/.

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This thesis investigated on-line inference generation in 7 to 10-year-old children. Using the Simple View of Reading (Gough & Tunmer, 1986) as a framework to classify reading disability, poor comprehenders and poor decoders were compared with chronological age-matched typical readers. In Experiments 1, 2, 3 and 4 a self-paced reading paradigm was employed to assess on-line inference generation. Reading times to target sentences that were consistent and inconsistent with inferred context were compared. Experiments 1 and 2 showed that children made inferences about fictional characters’ emotion-states and spatial inferences on-line, indexed by increased reading times to inconsistent target sentences. Results indicated that poor comprehenders made fewer inferences on-line than either typical readers or poor decoders. In Experiment 3, participants generated inferences based on early-acquired general knowledge on-line but not inferences based on later-acquired knowledge. This was replicated in Experiment 4 for early-acquired knowledge, however only poor comprehenders failed to generate inferences on-line using later-acquired knowledge. There was evidence of carry-over in post-target sentences, which was less pronounced in poor comprehenders. In Experiment 5, a self-paced listening paradigm showed that poor comprehenders generated fewer on-line inferences than typical readers did when processing spoken language, but contrary to prediction so did poor decoders. In Experiment 6, children read short vignettes followed by a question. They then evaluated four answers varying in plausibility. Poor comprehenders were equally accurate but responded faster than either poor decoders or typical readers. This was consistent with the view that poor comprehenders apply a lower standard for coherence when processing language. Together, the results support the view that decoding and linguistic comprehension dissociate, as predicted by the Simple View of Reading. These results contribute further evidence, using an on-line measure, that poor comprehenders generate fewer inferences than typical readers or poor decoders, and suggest this may be driven by the application of a lower standard for coherence when comprehending written or spoken language.
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Murza, Kimberly A. "Effects of a reading inference strategy intervention on the reading and social inference abilities of adults with Asperger syndrome." Doctoral diss., University of Central Florida, 2011. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4813.

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The ability to generate inferences is a skill that is necessary to fully comprehend a text and understand the intentions, behaviors, and emotions of a conversational partner. Individuals with Asperger syndrome (AS) have been shown to demonstrate significant difficulty in inference generation in both social contexts and in reading comprehension. Although, the reciprocity of the four components of literacy (reading, writing, listening, and speaking) has been established in the literature (Bradley & Bryant, 1983; Catts & Kamhi, 2005; Englert & Thomas, 1987; Gillon & Dodd, 1995; Hiebert, 1980; Kroll, 1981; Ruddell & Ruddell, 1994); the relationship between inference generation in reading and social inference generation is not well understood. The present study investigated the efficacy of a language-focused reading inference strategy intervention (ACT & Check Strategy) on the general reading comprehension, inference generation in reading, social inference, and metacognitive ability of adults with AS. Twenty-five adults with AS were randomly assigned to either a treatment or a control group. The treatment group participants were divided into groups of 3-4 based on their availability and preferred location for treatment resulting in a total of 4 groups. Each group met in one-hour sessions twice a week for a total of six weeks. When controlling for pretest scores, the treatment group was found to perform significantly better on one measure of inference generation in reading and metacognitive ability compared to the control group. Significant differences between groups were not found in two measures of inference generation in reading comprehension or social inference ability. These findings suggest that the ACT & Check strategy was effective in improving participants' ability to generate inferences as they read and their metacognitive reading ability. However, instruction in inference generation in reading does not appear to generalize to other language modalities (i.e., social inference generation). This research provides support for an explicit language-focused strategy intervention addressing the reading inference deficit area. Further research is warranted to investigate potential interventions to address social inference skills for individuals with AS.
ID: 030646242; System requirements: World Wide Web browser and PDF reader.; Mode of access: World Wide Web.; Thesis (Ph.D.)--University of Central Florida, 2011.; Includes bibliographical references (p. 287-309).
Ph.D.
Doctorate
Education and Human Performance
Education; Communication Sciences and Disorders Track
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Baretta, Luciane. "The process of inference making in reading comprehension." Florianópolis, SC, 2008. http://repositorio.ufsc.br/xmlui/handle/123456789/91884.

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Tese (doutorado) - Universidade Federal de Santa Catarina, Centro de Comunicação e Expressão. Programa de Pós-Graduação em Letras/Inglês e Literatura Correspondente.
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Pesquisas recentes na área de compreensão textual têm enfocado a habilidade dos leitores em construir uma representação mental coerente daquilo que lêem. Para que a representação uniforme de um texto seja obtida, o leitor deve ser capaz de compilar as informações presentes no texto com o seu conhecimento prévio para a construção do significado - que pode não estar explícito -, através do processo de inferência. Nesse estudo, o processo de inferência foi investigado mediante a leitura de dois tipos diferentes de texto, por meio da utilização da eletroencefalografia (EEG). Os sujeitos, falantes nativos do inglês, leram parágrafos expositivos e narrativos, e julgaram a plausibilidade da sentença final de cada parágrafo, tendo como referência, a informação das três sentenças anteriores. A análise dos resultados enfocou dois potenciais relacionados a eventos (ERPs): os componentes N1 e N400, e a acuidade nas respostas comportamentais. As amplitudes do N400 revelaram que o texto expositivo exigiu mais dos sujeitos em termos de processamento semântico, enquanto que as respostas comportamentais mostraram que os sujeitos tiveram uma tendência maior a gerar inferências enquanto liam esse mesmo tipo de texto. Com relação ao envolvimento dos hemisférios esquerdo e direito no processo de inferência, não houve diferenças significativas em relação à amplitude dos ERPs, embora o hemisfério direito tenha se mostrado mais participativo no momento em que os sujeitos liam a última sentença dos parágrafos, e tinham que julgar se a mesma era coerente com as sentenças anteriores. No geral, esse estudo sugere que os dois tipos de texto são processados diferentemente pelo cérebro, conforme demonstrado pelas nuances dos componentes N1 e N400, gerados durante a leitura das duas últimas sentenças de cada parágrafo. Embora não tenha sido possível uma clara visualização com relação aos processos cerebrais subjacentes ao processo de inferência, em função dos resultados pouco robustos, o presente estudo contribui como mais um dos primeiros passos a serem dados no longo caminho, até que uma compreensão mais detalhada dos processos cognitivos inerentes à compreensão textual seja alcançada. Much of recent research on discourse comprehension has centered on the readers' ability to construct coherent mental representations of texts. In order to form a unified representation of a given text, a reader must be able to join the information presented in the text with his background knowledge to construe the meaning that may not be explicitly stated in the text, through the generation of inferences. In this is study, the process of inference making by native speakers of English while reading two different types of text was investigated, using Electroencephalography (EEG). Subjects read narrative and expository paragraphs, and judged the plausibility of the final sentence of each four-sentence long paragraph by reference to the previous information. The analysis of data focused on two ERP (Event-related brain potential) components, the N1 and the N400 and on accuracy of behavioral responses. N400 amplitudes revealed that exposition was more demanding than narration in terms of semantic processing, whereas behavioral data showed that subjects were more prone to generate inferences when reading exposition. Concerning the involvement of the right and left hemispheres in the process of inference making, there were no significant differences in terms of the ERPs amplitudes, although the right hemisphere showed a tendency for greater participation when subjects were reading the last sentence of the paragraphs and had to judge whether this sentence was coherent to the previous sentences. Overall, this study suggests that the two types of text investigated are processed differently by the brain, as revealed by the nuances showed in the N1 and N400 components across the two last sentences of the paragraphs. Even though it was not possible to delineate a clear picture in terms of brain processes, given the lack of robust results, this study might be the first of many steps towards a complete understanding of the cognitive processes involved in discourse comprehension.
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El, Kaliouby Rana Ayman. "Mind-reading machines : automated inference of complex mental states." Thesis, University of Cambridge, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.615030.

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Zhang, Hao, and 張浩. "The generation of thematic inferences during narrative text comprehension." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hdl.handle.net/10722/210335.

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Zhang, Hao. "The generation of thematic inferences during narrative text comprehension." Click to view the E-thesis via HKUTO, 1998. http://sunzi.lib.hku.hk/hkuto/record/B4257481X.

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Lo, King-yan, and 盧景恩. "Do readers with autism spectrum disorder make inference in reading comprehension?" Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45589306.

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Bowyer-Crane, Claudine. "The relationship between reading comprehension and online inference generation in children." Thesis, University of York, 2002. http://etheses.whiterose.ac.uk/14165/.

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Szeto, Ngan-ha Christine. "The relationship between vocabulary development and reading and vocabulary learning strategies." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38718273.

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Hancock, Holly Elizabeth. "Aging and inferencing ability : an examination of factors underlying text comprehension." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/29558.

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Books on the topic "Inference reading"

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OBrien, Edward J., Anne E. Cook, and Jr Lorch, eds. Inferences during Reading. Cambridge: Cambridge University Press, 2015. http://dx.doi.org/10.1017/cbo9781107279186.

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Freedle, Roy O. The prediction of TOEFL reading comprehension item difficulty for expository prose passages for three item types--main idea, inference, and supporting idea items. Princeton, N.J: Educational Testing Service, 1993.

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What just happened? Reading results and making inferences. New York: Crabtree Pub., 2010.

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Challen, Paul C. What just happened? Reading results and making inferences. New York: Crabtree Pub., 2010.

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Meutsch, Dietrich. Inferenz- und Elaborationstypen beim literarischen Verstehen von Texten: Zum Einfluss von Lese- und Äusserungssituation auf ästhetische und polyvalente Verstehenshandlungen. Siegen: Institut für Empirische Literatur- und Medienforschung, 1985.

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O'Brien, Edward J., Anne E. Cook, and Lorch Robert F. Jr. Inferences During Reading. Cambridge University Press, 2015.

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Inferences during Reading. Cambridge University Press, 2017.

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Inference (Reading Passages That Build Comprehensio). Teaching Resources, 2005.

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Reading Between the Lines: Understanding Inference. Routledge, 2011.

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VanInwagen, Patricia Y. Inference Is a Guess You Make. Zephyr Press, 1997.

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Book chapters on the topic "Inference reading"

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Sugio, Takeshi. "Neural Mechanisms of Global Reading." In Diagrammatic Representation and Inference, 198–212. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44043-8_22.

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Fish, Andrew, and John Howse. "Towards a Default Reading for Constraint Diagrams." In Diagrammatic Representation and Inference, 51–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25931-2_8.

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Sugio, Takeshi, Atsushi Shimojima, and Yasuhiro Katagiri. "Psychological Evidence of Mental Segmentation in Table Reading." In Diagrammatic Representation and Inference, 124–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31223-6_16.

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Takemura, Ryo, Atsushi Shimojima, and Yasuhiro Katagiri. "A Logical Investigation on Global Reading of Diagrams." In Diagrammatic Representation and Inference, 330–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31223-6_42.

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Dau, Frithjof. "Fixing Shin’s Reading Algorithm for Peirce’s Existential Graphs." In Diagrammatic Representation and Inference, 88–92. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11783183_10.

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Song, Jun, Siliang Tang, Tianchi Qian, Wenwu Zhu, and Fei Wu. "Reading Document and Answering Question via Global Attentional Inference." In Advances in Multimedia Information Processing – PCM 2018, 335–45. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00776-8_31.

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Bier, Eric A., Edward W. Ishak, and Ed Chi. "Entity Workspace: An Evidence File That Aids Memory, Inference, and Reading." In Intelligence and Security Informatics, 466–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11760146_42.

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Koda, Keiko, and Ryan T. Miller. "Chapter 14. Cross-linguistic interactions in L2 word meaning inference in English as a foreign language." In Writing Systems, Reading Processes, and Cross-Linguistic Influences, 293–312. Amsterdam: John Benjamins Publishing Company, 2018. http://dx.doi.org/10.1075/bpa.7.14kod.

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Woolley, Gary. "Using Inferences and Strategic Processing." In Reading Comprehension, 99–109. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1174-7_7.

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Sasaki, Takashi. "Multiple Readings of Existential Graphs." In Diagrammatic Representation and Inference, 598–604. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91376-6_54.

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Conference papers on the topic "Inference reading"

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Wadhwa, Soumya, Varsha Embar, Matthias Grabmair, and Eric Nyberg. "Towards Inference-Oriented Reading Comprehension: ParallelQA." In Proceedings of the Workshop on Generalization in the Age of Deep Learning. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/w18-1001.

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Ghaeini, Reza, Sadid A. Hasan, Vivek Datla, Joey Liu, Kathy Lee, Ashequl Qadir, Yuan Ling, Aaditya Prakash, Xiaoli Fern, and Oladimeji Farri. "DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference." In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers). Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/n18-1132.

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Lin, Xuming, Ruifang Liu, and Yiwei Li. "An Option Gate Module for Sentence Inference on Machine Reading Comprehension." In CIKM '18: The 27th ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3269206.3269280.

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Zhang, Yuanxing, Yangbin Zhang, Kaigui Bian, and Xiaoming Li. "Towards Reading Comprehension for Long Documents." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/638.

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Machine reading comprehension has gained attention from both industry and academia. It is a very challenging task that involves various domains such as language comprehension, knowledge inference, summarization, etc. Previous studies mainly focus on reading comprehension on short paragraphs, and these approaches fail to perform well on the documents. In this paper, we propose a hierarchical match attention model to instruct the machine to extract answers from a specific short span of passages for the long document reading comprehension (LDRC) task. The model takes advantages from hierarchical-LSTM to learn the paragraph-level representation, and implements the match mechanism (i.e., quantifying the relationship between two contexts) to find the most appropriate paragraph that includes the hint of answers. Then the task can be decoupled into reading comprehension task for short paragraph, such that the answer can be produced. Experiments on the modified SQuAD dataset show that our proposed model outperforms existing reading comprehension models by at least 20% regarding exact match (EM), F1 and the proportion of identified paragraphs which are exactly the short paragraphs where the original answers locate.
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Li, Xiepeng, Zhexi Zhang, Wei Zhu, Zheng Li, Yuan Ni, Peng Gao, Junchi Yan, and Guotong Xie. "Pingan Smart Health and SJTU at COIN - Shared Task: utilizing Pre-trained Language Models and Common-sense Knowledge in Machine Reading Tasks." In Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/d19-6011.

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Wang, Bingning, Kang Liu, and Jun Zhao. "Conditional Generative Adversarial Networks for Commonsense Machine Comprehension." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/576.

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Recently proposed Story Cloze Test [Mostafazadeh et al., 2016] is a commonsense machine comprehension application to deal with natural language understanding problem. This dataset contains a lot of story tests which require commonsense inference ability. Unfortunately, the training data is almost unsupervised where each context document followed with only one positive sentence that can be inferred from the context. However, in the testing period, we must make inference from two candidate sentences. To tackle this problem, we employ the generative adversarial networks (GANs) to generate fake sentence. We proposed a Conditional GANs in which the generator is conditioned by the context. Our experiments show the advantage of the CGANs in discriminating sentence and achieve state-of-the-art results in commonsense story reading comprehension task compared with previous feature engineering and deep learning methods.
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Tomkins, Sabina, Jay Pujara, and Lise Getoor. "Disambiguating Energy Disaggregation: A Collective Probabilistic Approach." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/398.

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Reducing household energy usage is a priority for improving the resiliency and stability of the power grid and decreasing the negative impact of energy consumption on the environment and public health.Relevant and timely feedback about the power consumption of specific appliances can help household residents to reduce their energy demand. Given only a total energy reading, such as that collected from a residential meter, energy disaggregation strives to discover the consumption of individual appliances. Existing disaggregation algorithms are computationally inefficient and rely heavily on high-resolution ground truth data. We introduce a probabilistic framework which infers the energy consumption of individual appliances using a hinge-loss Markov random field (HL-MRF), which admits highly scalable inference. To further enhance efficiency, we introduce a temporal representation which leverages state duration. We also explore how contextual information impacts solution quality with low-resolution data. Our framework is flexible in its ability to incorporate additional constraints; by constraining appliance usage with context and duration we can better disambiguate appliances with similar energy consumption profiles. We demonstrate the effectiveness of our framework on two public real-world datasets, reducing the error relative to a previous state-of-the-art method by as much as 50%.
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Marotta, Claudio, Annalisa Milella, Grazia Cicirelli, and Arcangelo Distante. "Using a 2D Laser Range Finder for Environment Monitoring by an Autonomous Mobile Robot." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41385.

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In this paper, a novel approach to automated inspection is presented, which uses a mobile robot equipped with a 2D laser rangefinder. The main idea underlying the proposed method is that of comparing current laser readings with local range data of the environment stored in a database, to look for new or removed objects. First, the robot is guided to reach goals, fixed in critical areas where inspection is required. Range data of the region surrounding each goal are automatically acquired and stored in a database. Afterwards, the robot can begin its surveillance task. Each time it reaches a goal, comparison between the current readings and the stored local data is performed using an Iterative Closest Point (ICP)-based scan-matching algorithm. Then, a fuzzy logic inference system establishes whether a significant variation of the scene has occurred and an alarm signal must be produced. Experimental results show that the proposed approach is reliable in detecting either new or missing objects and can be effectively used in automated surveillance systems in dynamic environments.
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Han, Qilong, Dan Lu, and Rui Chen. "Fine-Grained Air Quality Inference via Multi-Channel Attention Model." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/346.

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In this paper, we study the problem of fine-grained air quality inference that predicts the air quality level of any location from air quality readings of nearby monitoring stations. We point out the importance of explicitly modeling both static and dynamic spatial correlations, and consequently propose a novel multi-channel attention model (MCAM) that models static and dynamic spatial correlations as separate channels. The static channel combines the beauty of attention mechanisms and graph-based spatial modeling via an adapted bilateral filtering technique, which considers not only locations' Euclidean distances but also their similarity of geo-context features. The dynamic channel learns stations' time-dependent spatial influence on a target location at each time step via long short-term memory (LSTM) networks and attention mechanisms. In addition, we introduce two novel ideas, atmospheric dispersion theories and the hysteretic nature of air pollutant dispersion, to better model the dynamic spatial correlation. We also devise a multi-channel graph convolutional fusion network to effectively fuse the graph outputs, along with other features, from both channels. Our extensive experiments on real-world benchmark datasets demonstrate that MCAM significantly outperforms the state-of-the-art solutions.
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Tuarob, Suppawong, and Conrad S. Tucker. "A Product Feature Inference Model for Mining Implicit Customer Preferences Within Large Scale Social Media Networks." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47225.

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The acquisition and mining of product feature data from online sources such as customer review websites and large scale social media networks is an emerging area of research. In many existing design methodologies that acquire product feature preferences form online sources, the underlying assumption is that product features expressed by customers are explicitly stated and readily observable to be mined using product feature extraction tools. In many scenarios however, product feature preferences expressed by customers are implicit in nature and do not directly map to engineering design targets. For example, a customer may implicitly state “wow I have to squint to read this on the screen”, when the explicit product feature may be a larger screen. The authors of this work propose an inference model that automatically assigns the most probable explicit product feature desired by a customer, given an implicit preference expressed. The algorithm iteratively refines its inference model by presenting a hypothesis and using ground truth data, determining its statistical validity. A case study involving smartphone product features expressed through Twitter networks is presented to demonstrate the effectiveness of the proposed methodology.
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Reports on the topic "Inference reading"

1

Kongsbak, Ute. Reading comprehension of literal, translational, and high inference level questions in aphasic and right hemisphere damaged adults. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5977.

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