-
Gillitzer, B.: Yewno (2017)
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- Abstract
- Yewno findet Themen und Konzepte (Suchbegriffe und ihre Abstraktionen) in englischsprachigen digitalen Texten mit Methoden des maschinellen Lernens und der künstlichen Intelligenz. Als Ergebnis Ihrer Suchanfrage werden die Konzepte, die Ihre Anfrage betreffen, in vielfältigen sachlichen Beziehungen als graphisches Netzwerk präsentiert, über das Sie einfach navigieren können. Auch versteckte thematische Beziehungen werden hier sichtbar gemacht, die vom Bekannten zu neuen Entdeckungen führen. Im Rahmen einer Pilotphase können Sie über einen interdisziplinären Ausschnitt aus aktuellen englischsprachigen Fachzeitschriften verschiedenster Fachgebiete recherchieren. Die zu den Themen gehörigen Artikel werden in Ausschnitten unmittelbar angezeigt und können in den meisten Fällen direkt als Volltext aufgerufen werden.
"Die Bayerische Staatsbibliothek testet den semantischen "Discovery Service" Yewno als zusätzliche thematische Suchmaschine für digitale Volltexte. Der Service ist unter folgendem Link erreichbar: https://www.bsb-muenchen.de/recherche-und-service/suchen-und-finden/yewno/. Das Identifizieren von Themen, um die es in einem Text geht, basiert bei Yewno alleine auf Methoden der künstlichen Intelligenz und des maschinellen Lernens. Dabei werden sie nicht - wie bei klassischen Katalogsystemen - einem Text als Ganzem zugeordnet, sondern der jeweiligen Textstelle. Die Eingabe eines Suchwortes bzw. Themas, bei Yewno "Konzept" genannt, führt umgehend zu einer grafischen Darstellung eines semantischen Netzwerks relevanter Konzepte und ihrer inhaltlichen Zusammenhänge. So ist ein Navigieren über thematische Beziehungen bis hin zu den Fundstellen im Text möglich, die dann in sogenannten Snippets angezeigt werden. In der Test-Anwendung der Bayerischen Staatsbibliothek durchsucht Yewno aktuell 40 Millionen englischsprachige Dokumente aus Publikationen namhafter Wissenschaftsverlage wie Cambridge University Press, Oxford University Press, Wiley, Sage und Springer, sowie Dokumente, die im Open Access verfügbar sind. Nach der dreimonatigen Testphase werden zunächst die Rückmeldungen der Nutzer ausgewertet. Ob und wann dann der Schritt von der klassischen Suchmaschine zum semantischen "Discovery Service" kommt und welche Bedeutung Anwendungen wie Yewno in diesem Zusammenhang einnehmen werden, ist heute noch nicht abzusehen. Die Software Yewno wurde vom gleichnamigen Startup in Zusammenarbeit mit der Stanford University entwickelt, mit der auch die Bayerische Staatsbibliothek eng kooperiert. [Inetbib-Posting vom 22.02.2017].
- Date
- 22. 2.2017 10:16:49
-
Nagao, M.: Knowledge and inference (1990)
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- RSWK
- Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
- Subject
- Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
-
Horch, A.; Kett, H.; Weisbecker, A.: Semantische Suchsysteme für das Internet : Architekturen und Komponenten semantischer Suchmaschinen (2013)
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- BK
- 54.72 Künstliche Intelligenz
- Classification
- 54.72 Künstliche Intelligenz
-
Hu, K.; Luo, Q.; Qi, K.; Yang, S.; Mao, J.; Fu, X.; Zheng, J.; Wu, H.; Guo, Y.; Zhu, Q.: Understanding the topic evolution of scientific literatures like an evolving city : using Google Word2Vec model and spatial autocorrelation analysis (2019)
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- Abstract
- Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.
-
Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002)
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- Date
- 22. 2.2003 17:25:39
22. 2.2003 18:17:40
-
Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983)
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- Date
- 30. 3.2001 13:32:22
-
Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016)
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- Date
- 1. 2.2016 18:25:22
-
Kozikowski, P. et al.: Support of part-whole relations in query answering (2016)
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- Date
- 1. 2.2016 18:25:22
-
Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Kopácsi, S. et al.: Development of a classification server to support metadata harmonization in a long term preservation system (2016)
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- Source
- Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
-
Sacco, G.M.: Dynamic taxonomies and guided searches (2006)
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- Date
- 22. 7.2006 17:56:22
-
Caro Castro, C.; Travieso Rodríguez, C.: Ariadne's thread : knowledge structures for browsing in OPAC's (2003)
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- Abstract
- Subject searching is the most common but also the most conflictive searching for end user. The aim of this paper is to check how users expressions match subject headings and to prove if knowledge structure used in online catalogs enhances searching effectiveness. A bibliographic revision about difficulties in subject access and proposed methods to improve it is also presented. For the empirical analysis, transaction logs from two university libraries, online catalogs (CISNE and FAMA) were collected. Results show that more than a quarter of user queries are effective due to an alphabetical subject index approach and browsing through hypertextual links. 1. Introduction Since the 1980's, online public access catalogs (OPAC's) have become usual way to access bibliographic information. During the last two decades the technological development has helped to extend their use, making feasible the access for a whole of users that is getting more and more extensive and heterogeneous, and also to incorporate information resources in electronic formats and to interconnect systems. However, technology seems to have developed faster than our knowledge about the tasks where it has been applied and than the evolution of our capacities for adapting to it. The conceptual model of OPAC has been hardly modified recently, and for interacting with them, users still need to combine the same skills and basic knowledge than at the beginning of its introduction (Borgman, 1986, 2000): a) conceptual knowledge to translate the information need into an appropriate query because of a well-designed mental model of the system, b) semantic and syntactic knowledge to be able to implement that query (access fields, searching type, Boolean logic, etc.) and c) basic technical skills in computing. At present many users have the essential technical skills to make use, with more or less expertise, of a computer. This number is substantially reduced when it is referred to the conceptual, semantic and syntactic knowledge that is necessary to achieve a moderately satisfactory search. An added difficulty arises in subject searching, as users should concrete their unknown information needs in terms that the information retrieval system can understand. Many researches have focused an unskilled searchers' difficulties to enter an effective query. The mental models influence, users assumption about characteristics, structure, contents and operation of the system they interact with have been analysed (Dillon, 2000; Dimitroff, 2000). Another issue that implies difficulties is vocabulary: how to find the right terms to implement a query and to modify it as the case may be. Terminology and expressions characteristics used in searching (Bates, 1993), the match between user terms and the subject headings from the catalog (Carlyle, 1989; Drabensttot, 1996; Drabensttot & Vizine-Goetz, 1994), the incidence of spelling errors (Drabensttot and Weller, 1996; Ferl and Millsap, 1996; Walker and Jones, 1987), users problems
-
Efthimiadis, E.N.: End-users' understanding of thesaural knowledge structures in interactive query expansion (1994)
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- Date
- 30. 3.2001 13:35:22
-
Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996)
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- Source
- Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon
-
Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998)
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- Date
- 1. 8.1996 22:08:06
-
Faaborg, A.; Lagoze, C.: Semantic browsing (2003)
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- Source
- Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Date
- 11. 2.2011 18:22:58
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005)
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- Date
- 11. 2.2011 18:22:25
-
Salaba, A.; Zeng, M.L.: Extending the "Explore" user task beyond subject authority data into the linked data sphere (2014)
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- 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
-
Mlodzka-Stybel, A.: Towards continuous improvement of users' access to a library catalogue (2014)
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- 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
