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Content

Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.

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Source

http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja

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Footnote

https%3A%2F%2Fjournals.univie.ac.at%2Findex.php%2Fvoebm%2Farticle%2Fdownload%2F5332%2F5271%2F&usg=AOvVaw2yQdFGHlmOwVls7ANCpTii.

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Abstract

On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.

Content

Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.

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Abstract

The successes of information retrieval (IR) in recent decades were built upon bag-of-words representations. Effective as it is, bag-of-words is only a shallow text understanding; there is a limited amount of information for document ranking in the word space. This dissertation goes beyond words and builds knowledge based text representations, which embed the external and carefully curated information from knowledge bases, and provide richer and structured evidence for more advanced information retrieval systems. This thesis research first builds query representations with entities associated with the query. Entities' descriptions are used by query expansion techniques that enrich the query with explanation terms. Then we present a general framework that represents a query with entities that appear in the query, are retrieved by the query, or frequently show up in the top retrieved documents. A latent space model is developed to jointly learn the connections from query to entities and the ranking of documents, modeling the external evidence from knowledge bases and internal ranking features cooperatively. To further improve the quality of relevant entities, a defining factor of our query representations, we introduce learning to rank to entity search and retrieve better entities from knowledge bases. In the document representation part, this thesis research also moves one step forward with a bag-of-entities model, in which documents are represented by their automatic entity annotations, and the ranking is performed in the entity space.
This proposal includes plans to improve the quality of relevant entities with a co-learning framework that learns from both entity labels and document labels. We also plan to develop a hybrid ranking system that combines word based and entity based representations together with their uncertainties considered. At last, we plan to enrich the text representations with connections between entities. We propose several ways to infer entity graph representations for texts, and to rank documents using their structure representations. This dissertation overcomes the limitation of word based representations with external and carefully curated information from knowledge bases. We believe this thesis research is a solid start towards the new generation of intelligent, semantic, and structured information retrieval.

Content

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.

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Abstract

In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.

Content

A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.

Date

10. 1.2013 19:22:47

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Footnote

Rez. in: Philosophisch-ethische Rezensionen vom 09.11.2019 (Jürgen Czogalla), Unter: https://philosophisch-ethische-rezensionen.de/rezension/Goedert1.html. In: B.I.T. online 23(2020) H.3, S.345-347 (W. Sühl-Strohmenger) [Unter: https%3A%2F%2Fwww.b-i-t-online.de%2Fheft%2F2020-03-rezensionen.pdf&usg=AOvVaw0iY3f_zNcvEjeZ6inHVnOK]. In: Open Password Nr. 805 vom 14.08.2020 (H.-C. Hobohm) [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzE0MywiOGI3NjZkZmNkZjQ1IiwwLDAsMTMxLDFd].

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Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

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Content

PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.

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Footnote

Vgl. unter: https://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=2ahUKEwizweHljdbcAhVS16QKHXcFD9QQFjABegQICRAB&url=https%3A%2F%2Fwww.researchgate.net%2Fpublication%2F271200105_Die_Autonomie_des_Menschen_und_der_Maschine_-_gegenwartige_Definitionen_von_Autonomie_zwischen_philosophischem_Hintergrund_und_technologischer_Umsetzbarkeit_Redigierte_Version_der_Magisterarbeit_Karls&usg=AOvVaw06orrdJmFF2xbCCp_hL26q.

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Content

Vgl. auch: New automatic interpreter for complex UDC numbers. Unter: <https%3A%2F%2Fudcc.org%2Ffiles%2FAttilaPiros_EC_36-37_2014-2015.pdf&usg=AOvVaw3kc9CwDDCWP7aArpfjrs5b>

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Abstract

With the growth in biomedical literature, the necessity of extracting useful information from the literature has increased. One approach to extracting biomedical knowledge involves using citation relations to discover entity relations. The assumption is that citation relations between any two articles connect knowledge entities across the articles, enabling the detection of implicit relationships among biomedical entities. The goal of this article is to examine the characteristics of biomedical entities connected via intermediate entities using citation relations aided by text mining. Based on the importance of symptoms as biomedical entities, we created triples connected via citation relations to identify drug-disease pairs with shared symptoms as intermediate entities. Drug-disease interactions built via citation relations were compared with co-occurrence-based interactions. Several types of analyses were adopted to examine the properties of the extracted entity pairs by comparing them with drug-disease interaction databases. We attempted to identify the characteristics of drug-disease pairs through citation relations in association with biomedical entities. The results showed that the citation relation-based approach resulted in diverse types of biomedical entities and preserved topical consistency. In addition, drug-disease pairs identified only via citation relations are interesting for clinical trials when they are examined using BITOLA.

Date

1.11.2018 18:19:22

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Abstract

There is greater depth in knowledge organization systems beyond the surface of hierarchically-structured concepts. Deconstructed elements of a knowledge organization system share network-like relationships that might be used in interaction with the characteristics of documents to provide "classification interaction" as a means of identifying previously undiscovered relationships. A random sample of UDC call numbers from the online catalog of the Catholic University of Leuven (KU Leuven) is analyzed to discover interactions among conceptual classification, instantiation, and bibliographic demographic characteristics. The associations demonstrated represent ways in which predictable interactions occur among classified bibliographic entities and the components of the rich UDC classification.

Source

Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik

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Abstract

What is the uniquely human factor in finding and using information to produce new knowledge? Is there an underlying aspect of our thinking that cannot be imitated by the AI-equipped machines that will increasingly dominate our lives? This book answers these questions, and tells us about our consciousness - its drive or intention in seeking information in the world around us, and how we are able to construct new knowledge from this information. The book is divided into three parts, each with an introduction and a conclusion that relate the theories and models presented to the real-world experience of someone using a search engine. First, Part I defines the exceptionality of human consciousness and its need for new information and how, uniquely among all other species, we frame our interactions with the world. Part II then investigates the problem of finding our real information need during information searches, and how our exceptional ability to frame our interactions with the world blocks us from finding the information we really need. Lastly, Part III details the solution to this framing problem and its operational implications for search engine design for everyone whose objective is the production of new knowledge. In this book, Charles Cole deliberately writes in a conversational style for a broader readership, keeping references to research material to the bare minimum. Replicating the structure of a detective novel, he builds his arguments towards a climax at the end of the book. For our video-game, video-on-demand times, he has visualized the ideas that form the book's thesis in over 90 original diagrams. And above all, he establishes a link between information need and knowledge production in evolutionary psychology, and thus bases his arguments in our origins as a species: how we humans naturally think, and how we naturally search for new information because our consciousness drives us to need it.

Footnote

Weitere Rez. unter: https://crl.acrl.org/index.php/crl/article/view/17830/19659: "Author Charles Cole's understanding of human consciousness is built foundationally upon the work of evolutionary psychologist Merlin Donald, who visualized the development of human cognition in four phases, with three transitions. According to Donald's Theory of Mind, preceding types of cognition do not cease to exist after human cognition transitions to a new phase, but exist as four layers within the modern consciousness. Cole's narrative in the first part of the book recounts Donald's model of human cognition, categorizing episodic, mimetic, mythic, and theoretic phases of cognition. The second half of the book sets up a particular situation of consciousness using the frame theory of Marvin Minsky, uses Meno's paradox (how can we come to know that which we don't already know?) in a critique of framing as Minsky conceived it, and presents group and national level framing and shows their inherent danger in allowing information avoidance and sanctioning immoral actions. Cole concludes with a solution of information need being sparked or triggered that takes the human consciousness out of a closed information loop, driving the consciousness to seek new information.
Cole's reliance upon Donald's Theory of Mind is limiting; it represents a major weakness of the book. Donald's Theory of Mind has been an influential model in evolutionary psychology, appearing in his 1991 book Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition (Harvard University Press). Donald's approach is a top-down, conceptual model that explicates what makes the human mind different and exceptional from other animal intelligences. However, there are other alternative, useful, science-based models of animal and human cognition that begin with a bottom-up approach to understanding the building blocks of cognition shared in common by humans and other "intelligent" animals. For example, in "A Bottom-Up Approach to the Primate Mind," Frans B.M. de Waal and Pier Francesco Ferrari note that neurophysiological studies show that specific neuron assemblies in the rat hippocampus are active during memory retrieval and that those same assemblies predict future choices. This would suggest that episodic memory and future orientation aren't as advanced a process as Donald posits in his Theory of Mind. Also, neuroimaging studies in humans show that the cortical areas active during observations of another's actions are related in position and structure to those areas identified as containing mirror neurons in macaques. Could this point to a physiological basis for imitation? ... (Scott Curtis)"

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Abstract

Words symbolically represent communicative and behavioral intent, and can provide clues to a communicator's future actions in online communication. This paper describes a sociotechnical study conducted from 2008 through 2015 to identify deceptive communicative intent within group context as manifested in language-action cues. Specifically, this study used an online team-based game that simulates real-world deceptive insider scenarios to examine several dimensions of group communication. First, we studied how language-action cues differ between groups with and groups without a compromised actor. We also examine how these cues differ within groups in terms of the group members' individual and collective interactions with the compromised actor. Finally, we look at how the cues of compromised actors differ from those of noncompromised actors, and how communication behavior changes after an actor is presented with an ethical dilemma. The results of the study further our understanding of language-action cues as indicators for unmasking a potential deceptive insider.

Date

16.11.2017 13:02:22

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Abstract

The proliferation of digital knowledge repositories (DKRs) used for distributed and collocated work raises important questions about how to manage these technologies. This study investigates why individuals contribute information to DKRs by applying and extending transactive memory theory. Data from knowledge workers (N = 208) nested in work groups (J = 17) located in Europe and the United States revealed, consistent with transactive memory theory, that perceptions of experts' retrieval of information were positively related to the likelihood of information provision to DKRs. The relationship between experts' perceptions of retrieval and information provision varied from group to group, and cross-level interactions indicated that trust in how the information would be used and the interdependence of tasks within groups could explain that variation. Furthermore, information provision to DKRs was related to communication networks in ways consistent with theorizing regarding the formation of transactive memory systems. Implications for theory and practice are discussed, emphasizing the utility of multilevel approaches for conceptualizing and modeling why individuals provide information to DKRs.

Date

22. 3.2013 19:39:00

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Abstract

Purpose - The purpose of this paper is to investigate user experiences with a touch-wall interface featuring both clustering and categorization representations of available e-books in a public library to understand human information interactions under work-focused and recreational contexts. Design/methodology/approach - Researchers collected questionnaires from 251 New Taipei City Library visitors who used the touch-wall interface to search for new titles. The authors applied structural equation modelling to examine relationships among hedonic/utilitarian needs, clustering and categorization representations, perceived ease of use (EU) and the extent to which users experienced anxiety and uncertainty (AU) while interacting with the interface. Findings - Utilitarian users who have an explicit idea of what they intend to find tend to prefer the categorization interface. A hedonic-oriented user tends to prefer clustering interfaces. Users reported EU regardless of which interface they engaged with. Results revealed that use of the clustering interface had a negative correlation with AU. Users that seek to satisfy utilitarian needs tended to emphasize the importance of perceived EU, whilst pleasure-seeking users were a little more tolerant of anxiety or uncertainty. Originality/value - The Online Public Access Catalogue (OPAC) encourages library visitors to borrow digital books through the implementation of an information visualization system. This situation poses an opportunity to validate uses and gratification theory. People with hedonic/utilitarian needs displayed different risk-control attitudes and affected uncertainty using the interface. Knowledge about user interaction with such interfaces is vital when launching the development of a new OPAC.

Date

20. 1.2015 18:30:22

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Abstract

Large amounts of health-related information of different types are available on the web. In addition to authoritative health information sites maintained by government health departments and healthcare institutions, there are many social media sites carrying user-contributed information. This study sought to identify the types of drug information available on consumer-contributed drug review sites when compared with authoritative drug information websites. Content analysis was performed on the information available for nine drugs on three authoritative sites (RxList, eMC, and PDRhealth) as well as three drug review sites (WebMD, RateADrug, and PatientsLikeMe). The types of information found on authoritative sites but rarely on drug review sites include pharmacology, special population considerations, contraindications, and drug interactions. Types of information found only on drug review sites include drug efficacy, drug resistance experienced by long-term users, cost of drug in relation to insurance coverage, availability of generic forms, comparison with other similar drugs and with other versions of the drug, difficulty in using the drug, and advice on coping with side effects. Drug efficacy ratings by users were found to be different across the three sites. Side effects were vividly described in context, with user assessment of severity based on discomfort and effect on their lives.

Date

22. 1.2016 12:24:05

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Abstract

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Date

22. 8.2014 17:12:54

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Abstract

Although chat-based reference services have been studied for over a decade and guidelines have been developed for effective communication in virtual reference service, little is known about the actual sources of miscommunication in these interactions. Our study uses a conversation analytic framework to investigate the types of potential or actual problems in communication that occur between librarians and patrons in chat reference interactions at a university library. Conversation analysis methodology, as developed by Harvey Sacks, Emanuel Schegloff, and Gain Jefferson, provides an empirical basis for claims about problems with communication by investigating what the participants themselves display as problematic or potentially problematic. Based on a corpus of archived chat reference transcripts, we show what types of problems in communication are displayed in the interaction, primarily through repair initiations, whether the problems are resolved, and, if so, how. Sources of problems that were targeted by both librarians and patrons included mistyping, typing in the wrong window, ambiguous terminology, differences in expertise between patrons and librarians, and the difficulty of giving and following instructions while not copresent. We conclude with implications for the training of future librarians in performing chat reference interactions.