Relevant bibliographies by topics / Interactional data

Contents

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

Academic literature on the topic 'Interactional data'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Interactional data"

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Wortham, Stanton, Katherine Mortimer, Kathy Lee, Elaine Allard, and Kimberly Daniel White. "Interviews as interactional data." Language in Society 40, no. 1 (February 2011): 39–50. http://dx.doi.org/10.1017/s0047404510000874.

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AbstractInterviews are designed to gather propositional information communicated through reference and predication. Some lament the fact that interviews always include interactional positioning that presupposes and sometimes creates social identities and power relationships. Interactional aspects of interview events threaten to corrupt the propositional information communicated, and it appears that these aspects need to be controlled. Interviews do often yield useful propositional information, and interviewers must guard against the sometimes-corrupting influence of interactional factors. But we argue that the interactional aspects of interview events can also be valuable data. Interview subjects sometimes position themselves in ways that reveal something about the habitual positioning that characterizes individuals or groups. We illustrate the potential value of this interactional information by describing “payday mugging” stories told by interviewees in one New Latino Diaspora town. (Interview data, narrating events, transference)
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Kádár, Dániel Z. "Identity Formation in Ritual Interaction." International Review of Pragmatics 7, no. 2 (2015): 278–307. http://dx.doi.org/10.1163/18773109-00702006.

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This paper explores the (co-)construction of identities in ritual interaction, by focusing on the choice of interactional styles. ‘Interactional style’ describes a cluster of similar indexical actions within the interaction “frame” (Goffman, 1974) of a ritual. Ritual is a recurrent interaction type, which puts constraints on the individual’s “freedom” to construct their (and others’) identities, in a somewhat similar way to institutional interactions, which have been broadly studied in the field. However, the constraints posed by ritual interactions are different from institutional, and so by examining identity (co-)construction via interactional style choices in ritual contexts, this paper fills an important knowledge gap. I approach interactional style choices through the notions of “role” and “accountability”, and by placing ritual practices within Goffman’s (1981) participation framework. I use examples of heckling at performing arts events as data. By focusing on interactional style, the paper contributes to the present Special Issue dedicated to interactional styles across cultures.
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Reed, Darren J. "Dancing with Data: Introducing a Creative Interactional Metaphor." Sociological Research Online 25, no. 4 (December 26, 2019): 533–48. http://dx.doi.org/10.1177/1360780419892640.

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In this article, a dance metaphor is developed to deepen our understanding of the material, sensual, processual, and experiential potential of digital data relations. Premised upon Blumer’s notion of a sensitising concept, ballroom dance theory is applied to everyday use of the Apple Watch so as to prompt investigation of subtle interactional features of device use. The aim is to engender an inclusive umbrella concept while simultaneously stimulating questions of analysis of and access to small-scale and intimate moments of embodied behaviours in future interactional analysis. In so doing, the article contributes to the sociology of data relationality in everyday life, as well as constituent approaches such as science and technology studies and the interactional study of bodies and machines.
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Peltonen, Pauliina. "L2 fluency in spoken interaction: a case study on the use of other-repetitions and collaborative completions." AFinLA-e: Soveltavan kielitieteen tutkimuksia, no. 10 (July 2, 2018): 118–38. http://dx.doi.org/10.30660/afinla.73130.

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Second language (L2) speech fluency has usually been studied from an individual’s perspective with monologue speech samples, whereas fluency studies examining dialogue data, especially with focus on collaborative practices, have been rare. In the present study, the aim was to examine how participants maintain fluency collaboratively. Four Finnish upper secondary school students of English completed a problem-solving task in pairs, and their spoken interactions were analyzed qualitatively with focus on collaborative completions and other-repetions. The findings demonstrated that collaborative completions and other-repetitions contribute to interactional fluency by creating cohesion to the interaction. Collaborative completions were also used to help the interlocutor to overcome temporary (individual) disfluent phases. Overall, the findings suggest that individual and interactional fluency are intertwined in spoken interaction, which should be acknowledged in theoretical approaches to L2 fluency and in empirical studies examining L2 fluency in interactional contexts.
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Murdoch, Jamie, Fiona Poland, and Charlotte Salter. "Analyzing Interactional Contexts in a Data-Sharing Focus Group." Qualitative Health Research 20, no. 5 (February 12, 2010): 582–94. http://dx.doi.org/10.1177/1049732310361612.

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Suryati, Nunung. "Indonesian Efl Teachers’ Practice Of Interactional Feedback." KnE Social Sciences 1, no. 3 (April 13, 2017): 489. http://dx.doi.org/10.18502/kss.v1i3.771.

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<p>Interactional feedback is defined as feedback that is generated by teachers in response to both erroneous and communicatively inappropriate utterances that students produce during conversational interaction (Nassaji, 2015). Interactional feedback has been investigated in second language acquisition contexts, but little has been done concerning interactional feedback in foreign language settings, particularly in Indonesian context. In this descriptive study, conducted at junior high school level, it was aimed to identify the actual practice of instructors of English as a foreign language on interactional feedback in their classrooms. A classroom observation protocol was used to collect the data. The results show that teachers in general have applied different types of interactional feedback. However, not all interactional feedback results in students’ uptakes.</p>
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Svahn, Johanna, and Ann-Carita Evaldsson. "‘You could just ignore me’: Situating peer exclusion within the contingencies of girls’ everyday interactional practices." Childhood 18, no. 4 (September 9, 2011): 491–508. http://dx.doi.org/10.1177/0907568211402859.

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The present article approaches the phenomenon of indirect bullying through detailed analysis of the interactional practices that a group of preadolescent girls make use of as they reconstruct the social organization of their peer group, the effect being that one girl is eventually excluded. The data are drawn from ethnography combined with video recordings of the girls’ peer group interactions in a Swedish elementary school, during one school year. The interactional data cover three different periods of the exclusion process. Overall, the study highlights how processes of social exclusion are situated within the flow of subtle and seemingly innocent actions that are embedded in ordinary everyday interactional peer group practices.
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Ziegler, Nicole, and Huy Phung. "Technology-mediated task-based interaction." Technology-mediated feedback and instruction 170, no. 2 (October 8, 2019): 251–76. http://dx.doi.org/10.1075/itl.19014.zie.

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Abstract This exploratory study examines the extent to which mode differentially impacts the quantity and quality of interactional features in second language (L2) task-based interaction. Following a within-subject, repeated measures design, intermediate adult learners (n = 20) completed four (counter-balanced) tasks with a confederate interlocutor in the following conditions: audio-chat, video-chat, text-chat, and multimodal chat (in which participants could interact using more than one form of communication). Quantitative analyses examined the quality of learners’ interactions, including negotiation, recasts, and LREs. Data regarding learners’ perceptions of type of technology were also collected to provide a more holistic perspective. The results demonstrate differences in terms of interactional features and learners’ preference based on mode of technology.
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Mortensen, Kristine Køhler. "Informed consent in the field of language and sexuality." Journal of Language and Sexuality 4, no. 1 (March 30, 2015): 1–29. http://dx.doi.org/10.1075/jls.4.1.01mor.

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In order to understand how sexual and romantic relations are established and negotiated in discourse, the field of language and sexuality is dependent upon empirical data from naturally occurring spontaneous interaction. However, detailed discussions of research methods are lacking in the field. In this article, I explore ways of accessing intimate spontaneous data in a heterosexual online dating context. Through interactional analysis of three types of online dating interaction, I examine the multi-faceted context for securing informed consent while at the same time preserving participants’ intimacy. I argue that institutionalized informed consent procedures may undercut participant agency and expose symbolic violence towards their carefully built interactional framework. The analysis demonstrates participants’ ability to negotiate ethical issues and to turn such issues into a contribution to the ongoing flirtatious interaction. As a result, I suggest a method that integrates participants’ interactional expertise in the consent-gaining process.
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Navaz, Abdul Majeed Mohamed. "Developing Interaction in ESL Classes: An Investigation of Teacher-Student Interaction of Teacher Trainees in a Sri Lankan University." International Journal of Learning, Teaching and Educational Research 20, no. 2 (February 28, 2021): 174–96. http://dx.doi.org/10.26803/ijlter.20.2.10.

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This study examines the possibility of using of IRF (Initiation-Response-Follow-up) sequence of teacher-student interaction in Sri Lankan ESL (English as a Second Language) classes for developing longer interactional exchanges which are believed to be useful for language development. Usually, in Sri Lankan ESL classes, teachers ask more display questions and a few referential questions. As a result, teacher-student interaction occurs only occasionally and they follow the traditional IRF pattern with an evaluation at the third move. Teachers could develop longer interactional exchanges by giving follow-up questions or prompts at the third move of the IRF sequence so that students respond, elaborate, explain or prolong their responses. This study examines how the teacher trainees on their teaching practice of a TESL degree programme at a university interacted with their students in ESL classes and how they changed their pattern of interaction to sustain more student interaction. Using lecture discourse data as the basis of the analysis, this study evaluated the changes after an intervention that focussed on training the teacher trainees in developing longer interactional episodes. The results revealed that there was only a slight improvement in the way teacher trainees maintained interactions in the lessons after the intervention. Hence, this study enlightens the possibility of utilizing interaction for language development through intensive teacher training.
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Dissertations / Theses on the topic "Interactional data"

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Lozano, Prieto David. "Data analysis and visualization of the 360degrees interactional datasets." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-88985.

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Nowadays, there has been an increasing interest in using 360degrees video in medical education. Recent efforts are starting to explore how nurse students experience and interact with 360degrees videos. However, once these interactions have been registered in a database, there is a lack of ways to analyze these data, which generates a necessity of creating a reliable method that can manage all this collected data, and visualize the valuable insights of the data. Hence, the main goal of this thesis is to address this challenge by designing an approach to analyze and visualize this kind of data. This will allow teachers in health care education, and medical specialists to understand the collected data in a meaningful way. To get the most suitable solution, several meetings with nursing teachers took place to draw the first draft structure of an application which acts as the needed approach. Then, the application was used to analyze collected data in a study made in December. Finally, the application was evaluated through a questionnaire that involved a group of medical specialists related to education. The initial outcome from those testing and evaluations indicate that the application successfully achieves the main goals of the project, and it has allowed discussing some ideas that will help in the future to improve the 360degrees video experience and evaluation in the nursing education field providing an additional tool to analyze, compare and assess students.
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Hannila, H. (Hannu). "Towards data-driven decision-making in product portfolio management:from company-level to product-level analysis." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526224428.

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Abstract Products and services are critical for companies as they create the foundation for companies’ financial success. Twenty per cent of company products typically account for some eighty per cent of sales volume. Nevertheless, the product portfolio decisions — how to strategically renew company product offering — tend to involve emotions, pet products and who-shout-the-loudest mentality while facts, numbers, and quantitative analyses are missing. Profitability is currently measured and reported at a company level, and firms seem unable to measure product-level profitability in a constant way. Consequently, companies are unable to maintain and renew their product portfolio in a strategically or commercially balanced way. The main objective of this study is to provide a data-driven product portfolio management (PPM) concept, which recognises and visualises in real-time and based on facts which company products are concurrently strategic and profitable, and what is the share of them in the product portfolio. This dissertation is a qualitative study to understand the topical area by the means combining literature review, company interviews, observations, and company internal material, to take steps towards data-driven decision-making in PPM. This study indicates that company data assets need to be combined and governed company-widely to realise the full potential of company strategic assets — the DATA. Data must be governed separately from business IT technology and beyond it. Beyond data and technology, the data-driven company culture must be adopted first. The data-driven PPM concept connects key business processes, business IT systems and several concepts, such as productization, product lifecycle management and PPM. The managerial implications include, that the shared understanding of the company products is needed, and the commercial and technical product structures are created accordingly, as they form the backbone of the company business as the skeleton to gather all product-related business-critical information for product-level profitability analysis. Also, product classification for strategic, supportive and non-strategic is needed, since the strategic nature of the product can change during the entire product lifecycle, e.g. due to the technology obsolescence, disruptive innovations by competitors, or for any other reason
Tiivistelmä Tuotteet ja palvelut ovat yrityksille kriittisiä, sillä ne luovat perustan yritysten taloudelliselle menestykselle. Kaksikymmentä prosenttia yrityksen tuotteista edustaa tyypillisesti noin kahdeksaakymmentä prosenttia myyntimääristä. Siitä huolimatta tuoteporfoliopäätöksiin — kuinka strategisesti uudistetaan yrityksen tuotetarjoomaa — liittyy tunteita, lemmikkituotteita ja kuka-huutaa-kovimmin -mentaliteettia faktojen, numeroiden ja kvantitatiivisten analyysien puuttuessa. Kannattavuutta mitataan ja raportoidaan tällä hetkellä yritystasolla, ja yritykset eivät näyttäisi pystyvän mittaamaan tuotetason kannattavuutta johdonmukaisesti. Tämä estää yrityksiä ylläpitämästä ja uudistamasta tuotevalikoimaansa strategisesti tai kaupallisesti tasapainoisella tavalla. Tämän tutkimuksen päätavoite on tarjota dataohjattu (data-driven) tuoteportfoliohallinnan konsepti, joka tunnistaa ja visualisoi reaaliajassa ja faktapohjaisesti, mitkä yrityksen tuotteet ovat samanaikaisesti strategisia ja kannattavia ja mikä on niiden osuus tuoteportfoliossa. Tämä väitöskirja on laadullinen tutkimus, jossa yhdistyy kirjallisuuskatsaus, yrityshaastattelut, havainnot ja yritysten sisäinen dokumentaatio, joiden pohjalta pyritään kohti dataohjautuvaa päätöksentekoa tuoteportfolion hallinnassa. Tämä tutkimus osoittaa, että yrityksen data assettit on yhdistettävä ja hallittava yrityksenlaajuisesti, jotta yrityksen strategisten assettien — DATAN — potentiaali voidaan hyödyntää kokonaisuudessaan. Data on hallittava erillään yrityksen IT-teknologiasta ja sen yläpuolella. Ennen dataa ja teknologiaa on omaksuttava dataohjattu yrityskulttuuri. Dataohjatun tuoteportfolionhallinnan konsepti yhdistää keskeiset liiketoimintaprosessit, liiketoiminnan IT-järjestelmät ja useita konsepteja, kuten tuotteistaminen, tuotteen elinkaaren hallinta ja tuoteportfolion hallinta. Yhteisymmärrys yrityksen tuotteista ja sekä kaupallisen että teknisen tuoterakenteet luominen vastaavasti on ennakkoedellytys dataohjatulle tuoteportfolion hallinnalle, koska ne muodostavat yrityksen liiketoiminnan selkärangan, joka yhdistää kaikki tuotteisiin liittyvät liiketoimintakriittiset tiedot tuotetason kannattavuuden analysoimiseksi. Lisäksi tarvitaan tuotteiden kategorisointi strategisiin, tukeviin ja ei-strategisiin tuotteisiin, koska tuotteen strateginen luonne voi muuttua tuotteen elinkaaren aikana, johtuen esimerkiksi teknologian vanhenemisesta, kilpailijoiden häiritsevistä innovaatioista tai mistä tahansa muusta syystä
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Xue, Vincent. "Modeling and designing Bc1-2 family protein interactions using high-throughput interaction data." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120446.

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Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 153-164).
Protein-protein interactions (PPIs) play a major role in cellular function, mediating signal processing and regulating enzymatic activity. Understanding how proteins interact is essential for predicting new binding partners and engineering new functions. Mutational analysis is one way to study the determinants of protein interaction. Traditionally, the biophysical study of protein interactions has been limited by the number of mutants that could be made and analyzed, but advances in high-throughput sequencing have enabled rapid assessment of thousands of variants. The Keating lab has developed an experimental protocol that can rank peptides based on their binding affinity for a designated receptor. This technique, called SORTCERY, takes advantage of cell sorting and deep-sequencing technologies to provide more binding data at a higher resolution than has previously been achievable. New computational methods are needed to process and analyze the high-throughput datasets. In this thesis, I show how experimental data from SORTCERY experiments can be processed, modeled, and used to design novel peptides with select specificity characteristics. I describe the computational pipeline that I developed to curate the data and regression models that I constructed from the data to relate protein sequence to binding. I applied models trained on experimental data sets to study the peptide-binding specificity landscape of the Bc1-xL, Mc1-1, and Bf1-1 anti-apoptotic proteins, and I designed novel peptides that selectively bind tightly to only one of these receptors, or to a pre-specified combination of receptors. My thesis illustrates how data-driven models combined with high-throughput binding assays provide new opportunities for rational design.
by Vincent Xue.
Ph. D.
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Popov, Igor. "End-user data-centric interactions over linked data." Thesis, University of Southampton, 2013. https://eprints.soton.ac.uk/361729/.

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The ability to build tools that support gathering and querying information from distributed sources on the Web rests on the availability of structured data. Linked Data, as a way for publishing and linking distributed structured data sources on the Web, provides an opportunity to create this kind of tools. Currently, however, the ability to complete such tasks over Linked Data sources is limited to users with advanced technical skills, resulting in an online information space largely inaccessible to non-technical end users. This thesis explores the challenges of designing user interfaces for end users, those without technical skills, to use Linked Data to solve information tasks that require combining information from multiple sources. The thesis explores the design space around interfaces that support access to Linked Data on demand, suggests potential use cases and stakeholders, and proposes several direct manipulation tools for end users with diverse needs and skills. User studies indicate that the tools built offer solutions to various challenges in accessing Linked Data that are identified in this thesis.
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Carlsson, Nicole. "Vulnerable data interactions — augmenting agency." Thesis, Malmö universitet, Fakulteten för kultur och samhälle (KS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23309.

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This thesis project opens up an interaction design space in the InfoSec domain concerning raising awareness of common vulnerabilities and facilitating counter practices through seamful design.This combination of raising awareness coupled with boosting possibilities for deliberate action (or non-action) together account for augmenting agency. This augmentation takes the form of bottom up micro-movements and daily gestures contributing to opportunities for greater agency in the increasingly fraught InfoSec domain.
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Elhageen, Adel Abdelfatah M. "Effect of interaction between parental treatment styles and peer relations in classroom on the feelings of loneliness among deaf children in Egyptian schools /." Berlin : WVB Wissenschaftlicher Verlag, 2005. http://www.wvberlin.de/data/inhalt/elhageen.htm.

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Rodriguez, Perdomo Carlos Mario. "Designing interactions for data obfuscation in IoT." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-22494.

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This project explores the internet of things (IoT) at home, especially the aspects related to the quantity and the quality of the of data collected by the smart devices and the violation of the users’ privacy this situation represents, since with the help of machine learning algorithms, these devices are capable of storing and analysing information related to the daily routine of each user at home. Therefore, this research enquires new ways to raise the user's’ awareness about the flow of the data within the IoT at home in order to empower them and give them back the status of administrators of this context by designing devices that are capable of obfuscating the data before it leaves the home.During this process, several methods were used together in order to reach the outcomes. From the use of annotated portfolios to evaluate the state of the art related with the field, to video sketching as a useful and quick tool to embrace the user’s perspective in parallel with the use of cultural probes in order to test some conceptual scenarios and find new ways to explore this project based on the experiences of the participants.As a result, this project’s outcome is based on the use of the materialization of the data as the proper way to bring the abstract process that happens in the background closer to the user's reality in order to display how this data is actually flowing through the environment and at the end generate a call­to­action to guide the user into the execution of the obfuscation of the data.This project opens up the discussion within the interaction design field about the way we are communicating with the technology and if it is the proper way to do it when this technology coexist with the user at home. Additionally, it questions the way in which the interfaces should be designed in order to create a transparent dialogue between the users, the objects and the vendors.
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Fischer, Manfred M., and Daniel A. Griffith. "Modelling spatial autocorrelation in spatial interaction data." WU Vienna University of Economics and Business, 2007. http://epub.wu.ac.at/3948/1/SSRN%2Did1102183.pdf.

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Spatial interaction models of the gravity type are widely used to model origindestination flows. They draw attention to three types of variables to explain variation in spatial interactions across geographic space: variables that characterise an origin region of a flow, variables that characterise a destination region of a flow, and finally variables that measure the separation between origin and destination regions. This paper outlines and compares two approaches, the spatial econometric and the eigenfunction-based spatial filtering approach, to deal with the issue of spatial autocorrelation among flow residuals. An example using patent citation data that capture knowledge flows across 112 European regions serves to illustrate the application and the comparison of the two approaches.(authors' abstract)
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Thomas, Helen. "Enabling scalable online user interaction management through data warehousing of interaction histories / by Helen Thomas." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/29873.

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Liu, Chunmei 1970. "Cross-layer protocol interactions in heterogeneous data networks." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/28918.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.
Includes bibliographical references (p. 143-148).
(cont.) TCP timeout backoff and MAC layer retransmissions, are studied in detail. The results show that the system performance is a balance of idle slots and collisions at the MAC layer, and a tradeoff between packet loss probability and round trip time at the transport layer. Finally, we consider the optimal scheduling problem with window service constraints. Optimal policies that minimize the average response time of jobs are derived and the results show that both the job lengths and the window sizes are essential to the optimal policy.
Modern data networks are heterogeneous in that they often employ a variety of link technologies, such as wireline, optical, satellite and wireless links. As a result, Internet protocols, such as Transmission Control Protocol (TCP), that were designed for wireline networks, perform poorly when used over heterogeneous networks. This is particularly the case for satellite and wireless networks which are often characterized by high bandwidth-delay product and high link loss probability. This thesis examines the performance of TCP in the context of heterogeneous networks, particularly focusing on interactions between protocols across different layers of the protocol stack. First, we provide an analytical framework to study the interaction between TCP and link layer retransmission protocols (ARQ). The system is modelled as a Markov chain with reward functions, and detailed queueing models are developed for the link layer ARQ. The analysis shows that in most cases implementing ARQ can achieve significant improvement in system throughput. Moreover, by proper choice of protocols parameters, such as the packet size and the number of transmission attempts per packet, significant performance improvement can be obtained. We then investigate the interaction between TCP at the transport layer and ALOHA at the MAC layer. Two equations are derived to express the system performance in terms of various system and protocol parameters, which show that the maximum possible system throughput is 1/e. A sufficient and necessary condition to achieve this throughput is also presented, and the optimal MAC layer transmission probability at which the system achieves its highest throughput is given. Furthermore, the impact of other system and protocol parameters, such as
by Chunmei Liu.
Ph.D.
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Books on the topic "Interactional data"

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Cao, Longbing, Yifeng Zeng, Andreas L. Symeonidis, Vladimir Gorodetsky, Jörg P. Müller, and Philip S. Yu, eds. Agents and Data Mining Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55192-5.

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Cao, Longbing, Yifeng Zeng, Bo An, Andreas L. Symeonidis, Vladimir Gorodetsky, Frans Coenen, and Philip S. Yu, eds. Agents and Data Mining Interaction. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20230-3.

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Cao, Longbing, Vladimir Gorodetsky, Jiming Liu, Gerhard Weiss, and Philip S. Yu, eds. Agents and Data Mining Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03603-3.

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Cao, Longbing, Yifeng Zeng, Andreas L. Symeonidis, Vladimir I. Gorodetsky, Philip S. Yu, and Munindar P. Singh, eds. Agents and Data Mining Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36288-0.

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Cao, Longbing, Ana L. C. Bazzan, Vladimir Gorodetsky, Pericles A. Mitkas, Gerhard Weiss, and Philip S. Yu, eds. Agents and Data Mining Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15420-1.

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Cao, Longbing, Ana L. C. Bazzan, Andreas L. Symeonidis, Vladimir I. Gorodetsky, Gerhard Weiss, and Philip S. Yu, eds. Agents and Data Mining Interaction. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27609-5.

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Cannataro, Mario, and Pietro Hiram Guzzi. Data Management of Protein Interaction Networks. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118103746.

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1980-, Guzzi Pietro Hiram, ed. Data management of protein interaction networks. Hoboken, NY: Wiley, 2012.

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Oberholzner, Werner. SWADE data guide. Greenbelt, Md: National Aeronautics and Space Administration, Goddard Space Flight Center, 1996.

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Mulvihill, C. G. Group interaction support. Dublin: University College Dublin, 1996.

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Book chapters on the topic "Interactional data"

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Jamieson, Jack, and Jeffrey Boase. "Listening to Social Rhythms: Exploring Logged Interactional Data Through Sonification." In The SAGE Handbook of Social Media Research Methods, 405–19. 1 Oliver's Yard, 55 City Road London EC1Y 1SP: SAGE Publications Ltd, 2016. http://dx.doi.org/10.4135/9781473983847.n24.

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Blache, Philippe, Roxane Bertrand, Gaëlle Ferré, Berthille Pallaud, Laurent Prévot, and Stéphane Rauzy. "The Corpus of Interactional Data: A Large Multimodal Annotated Resource." In Handbook of Linguistic Annotation, 1323–56. Dordrecht: Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-0881-2_51.

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Müller, Nicole. "Why Use Interactional Data to Better Understand the Effects of Dementia?" In Learning from the Talk of Persons with Dementia, 47–60. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43977-4_4.

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Schmitz, Andreas, Olga Yanenko, and Marcel Hebing. "Identifying Artificial Actors in E-Dating: A Probabilistic Segmentation Based on Interactional Pattern Analysis." In Challenges at the Interface of Data Analysis, Computer Science, and Optimization, 319–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24466-7_33.

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Hinneburg, Alexander, and Daniel A. Keim. "Visual Interaction." In Data Visualization, 407–21. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-1177-9_28.

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Pedley, J. B., R. D. Naylor, and S. P. Kirby. "Group Interactions." In Thermochemical Data of Organic Compounds, 52–63. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4099-4_4.

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Schmidt, Benedikt, and Eicke Godehardt. "Interaction Data Management." In Knowlege-Based and Intelligent Information and Engineering Systems, 402–9. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23863-5_41.

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Böhmelt, Tobias. "Main Data Source: The International Conflict Management Data." In International Mediation Interaction, 23–30. Wiesbaden: VS Verlag für Sozialwissenschaften, 2011. http://dx.doi.org/10.1007/978-3-531-92812-8_2.

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Aigner, Wolfgang, Silvia Miksch, Heidrun Schumann, and Christian Tominski. "Interaction Support." In Visualization of Time-Oriented Data, 105–26. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-079-3_5.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Interaction." In Clinical Data Analysis on a Pocket Calculator, 139–43. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27104-0_25.

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Conference papers on the topic "Interactional data"

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Razin, Yosef, and Karen Feigh. "Toward Interactional Trust for Humans and Automation: Extending Interdependence." In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI). IEEE, 2019. http://dx.doi.org/10.1109/smartworld-uic-atc-scalcom-iop-sci.2019.00247.

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Kriz, Sarah, Toni D. Ferro, Pallavi Damera, and John R. Porter. "Fictional robots as a data source in HRI research: Exploring the link between science fiction and interactional expectations." In 2010 RO-MAN: The 19th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 2010. http://dx.doi.org/10.1109/roman.2010.5598620.

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Zhang, Xiaowang, Qiang Gao, and Zhiyong Feng. "InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/602.

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In this paper, we present a neural network (InteractionNN) for sparse predictive analysis where hidden features of sparse data can be learned by multilevel feature interaction. To characterize multilevel interaction of features, InteractionNN consists of three modules, namely, nonlinear interaction pooling, layer-lossing, and embedding. Nonlinear interaction pooling (NI pooling) is a hierarchical structure and, by shortcut connection, constructs low-level feature interactions from basic dense features to elementary features. Layer-lossing is a feed-forward neural network where high-level feature interactions can be learned from low-level feature interactions via correlation of all layers with target. Moreover, embedding is to extract basic dense features from sparse features of data which can help in reducing our proposed model computational complex. Finally, our experiment evaluates on the two benchmark datasets and the experimental results show that InteractionNN performs better than most of state-of-the-art models in sparse regression.
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Flesch, Benjamin Johannes. "Social Interaction Model." In 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. http://dx.doi.org/10.1109/bigdata.2018.8622346.

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Balma, Jacob, Aaron D. Vose, Yuri K. Peterson, Amar G. Chittiboyina, Pankaj Pandey, Charles R. Yates, Ikhlas A. Khan, and Sreenivas R. Sukumar. "Deep Learning Predicts Protein-Ligand Interactions." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9377868.

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Buck, Lauren E., and Bobby Bodenheimer. "Privacy and Personal Space: Addressing Interactions and Interaction Data as a Privacy Concern." In 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE, 2021. http://dx.doi.org/10.1109/vrw52623.2021.00086.

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Kim, Minkyu, Suan Lee, and Jinho Kim. "Combining Multiple Implicit-Explicit Interactions for Regression Analysis." In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 2020. http://dx.doi.org/10.1109/bigdata50022.2020.9378402.

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Strey, Mateus Rambo, Roberto Pereira, and Luciana C. de Castro Salgado. "Human Data-Interaction." In IHC 2018: 17th Brazilian Symposium on Human Factors in Computing Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3274192.3274219.

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Wang, Chenxiao, Jason Arenson, Florian Helff, Le Gruenwald, and Laurent d'Orazio. "Improving user interaction in mobile-cloud database query processing." In 2017 IEEE International Conference on Big Data (Big Data). IEEE, 2017. http://dx.doi.org/10.1109/bigdata.2017.8258208.

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Peuhkuri, Markus. "Toolbox to analyze computer-network interaction." In Voice, Video, and Data Communications, edited by Wai Sum Lai and Hisashi Kobayashi. SPIE, 1997. http://dx.doi.org/10.1117/12.290445.

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Reports on the topic "Interactional data"

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Schutt, Timothy, and Manoj Shukla. Predicting the impact of aqueous ions on fate and transport of munition compounds. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41481.

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A model framework for natural water has been developed using computational chemistry techniques to elucidate the interactions between solvated munition compounds and eight common ions in naturally occurring water sources. The interaction energies, residence times, coordination statistics, and surface preferences of nine munition related compounds with each ion were evaluated. The propensity of these interactions to increase degradation of the munition compound was predicted using accelerated replica QM/MM simulations. The degradation prediction data qualitatively align with previous quantum mechanical studies. The results suggest that primary ions of interest for fate and transport modeling of munition compounds in natural waters may follow the relative importance of SO₄²⁻, Cl⁻ ≫ HCO₃⁻, Na⁺, Mg²⁺ > Ca²⁺, K⁺, and NH₄⁺.
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Liu, Huan, Xufei Wang, Lei Tang, Sai Moturu, Nitin Agarwal, John Salerno, and Geoff Barbier. Modeling Group Interactions via Open Data Sources. Fort Belvoir, VA: Defense Technical Information Center, August 2011. http://dx.doi.org/10.21236/ada567932.

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Terrill, Eric J. CBLAST Data Analysis: Air-Sea Interaction Floats. Fort Belvoir, VA: Defense Technical Information Center, March 2009. http://dx.doi.org/10.21236/ada495437.

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Briscoe, William John, Igor I. Strakovsky, and Ronald L. Workman. A Data Analysis Center for Electromagnetic and Hadronic Interaction. Office of Scientific and Technical Information (OSTI), May 2015. http://dx.doi.org/10.2172/1213477.

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Smith, L. The Use of Man-Machine Interaction in Data-Fitting Problems. Office of Scientific and Technical Information (OSTI), June 2018. http://dx.doi.org/10.2172/1453868.

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Brand, A. G., N. M. Komerath, and H. M. McMahon. Wind Tunnel Data from a Rotor Wake/Airframe Interaction Study. Fort Belvoir, VA: Defense Technical Information Center, July 1986. http://dx.doi.org/10.21236/ada171333.

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Schildknecht, Thomas, and Monika Hager. Quantifying Space Environment Interactions with Debris Objects using Observation Data Fusion Techniques. Fort Belvoir, VA: Defense Technical Information Center, September 2014. http://dx.doi.org/10.21236/ada611570.

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Thomas, E. W. Atomic data for controlled fusion research. Volume III. Particle interactions with surfaces. Office of Scientific and Technical Information (OSTI), February 1985. http://dx.doi.org/10.2172/5959343.

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Moore, James A. Interaction of Typhoon and Ocean Project (ITOP) Data Management and Operations Support. Fort Belvoir, VA: Defense Technical Information Center, September 2012. http://dx.doi.org/10.21236/ada590521.

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Apitz, S. E., B. P. Ayers, and V. J. Kirtay. Use of Data on Contaminant/Sediment Interactions to Streamline Sediment Assessment and Management. Fort Belvoir, VA: Defense Technical Information Center, August 2004. http://dx.doi.org/10.21236/ada432474.

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