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  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Nagao, M.: Knowledge and inference (1990) 0.01
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    Abstract
    Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.
    Year
    1990
  2. Vechtomova, O.; Robertson, S.E.: ¬A domain-independent approach to finding related entities (2012) 0.01
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    Abstract
    We propose an approach to the retrieval of entities that have a specific relationship with the entity given in a query. Our research goal is to investigate whether related entity finding problem can be addressed by combining a measure of relatedness of candidate answer entities to the query, and likelihood that the candidate answer entity belongs to the target entity category specified in the query. An initial list of candidate entities, extracted from top ranked documents retrieved for the query, is refined using a number of statistical and linguistic methods. The proposed method extracts the category of the target entity from the query, identifies instances of this category as seed entities, and computes similarity between candidate and seed entities. The evaluation was conducted on the Related Entity Finding task of the Entity Track of TREC 2010, as well as the QA list questions from TREC 2005 and 2006. Evaluation results demonstrate that the proposed methods are effective in finding related entities.
  3. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005) 0.00
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    Abstract
    Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
    Date
    11. 2.2011 18:22:58
  4. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.00
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    Abstract
    Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
    Date
    11. 2.2011 18:22:25
  5. Brandão, W.C.; Santos, R.L.T.; Ziviani, N.; Moura, E.S. de; Silva, A.S. da: Learning to expand queries using entities (2014) 0.00
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    Abstract
    A substantial fraction of web search queries contain references to entities, such as persons, organizations, and locations. Recently, methods that exploit named entities have been shown to be more effective for query expansion than traditional pseudorelevance feedback methods. In this article, we introduce a supervised learning approach that exploits named entities for query expansion using Wikipedia as a repository of high-quality feedback documents. In contrast with existing entity-oriented pseudorelevance feedback approaches, we tackle query expansion as a learning-to-rank problem. As a result, not only do we select effective expansion terms but we also weigh these terms according to their predicted effectiveness. To this end, we exploit the rich structure of Wikipedia articles to devise discriminative term features, including each candidate term's proximity to the original query terms, as well as its frequency across multiple article fields and in category and infobox descriptors. Experiments on three Text REtrieval Conference web test collections attest the effectiveness of our approach, with gains of up to 23.32% in terms of mean average precision, 19.49% in terms of precision at 10, and 7.86% in terms of normalized discounted cumulative gain compared with a state-of-the-art approach for entity-oriented query expansion.
    Date
    22. 8.2014 17:07:50
  6. Robertson, S.E.: On term selection for query expansion (1990) 0.00
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    Source
    Journal of documentation. 46(1990) no.4, S.359-364
    Year
    1990
  7. Walker, S.; DeVere, R.: Improving subject retrieval in online catalogues : T.2: Relevance feedback and query expansion (1990) 0.00
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    Year
    1990
  8. Bradford, R.B.: Relationship discovery in large text collections using Latent Semantic Indexing (2006) 0.00
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    Abstract
    This paper addresses the problem of information discovery in large collections of text. For users, one of the key problems in working with such collections is determining where to focus their attention. In selecting documents for examination, users must be able to formulate reasonably precise queries. Queries that are too broad will greatly reduce the efficiency of information discovery efforts by overwhelming the users with peripheral information. In order to formulate efficient queries, a mechanism is needed to automatically alert users regarding potentially interesting information contained within the collection. This paper presents the results of an experiment designed to test one approach to generation of such alerts. The technique of latent semantic indexing (LSI) is used to identify relationships among entities of interest. Entity extraction software is used to pre-process the text of the collection so that the LSI space contains representation vectors for named entities in addition to those for individual terms. In the LSI space, the cosine of the angle between the representation vectors for two entities captures important information regarding the degree of association of those two entities. For appropriate choices of entities, determining the entity pairs with the highest mutual cosine values yields valuable information regarding the contents of the text collection. The test database used for the experiment consists of 150,000 news articles. The proposed approach for alert generation is tested using a counterterrorism analysis example. The approach is shown to have significant potential for aiding users in rapidly focusing on information of potential importance in large text collections. The approach also has value in identifying possible use of aliases.
    Source
    Proceedings of the Fourth Workshop on Link Analysis, Counterterrorism, and Security, SIAM Data Mining Conference, Bethesda, MD, 20-22 April, 2006. [http://www.siam.org/meetings/sdm06/workproceed/Link%20Analysis/15.pdf]
  9. Ingwersen, P.; Järvelin, K.: ¬The turn : integration of information seeking and retrieval in context (2005) 0.00
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    Footnote
    - Kapitel fünf enthält einen entsprechenden Überblick über die kognitive und benutzerorientierte IR-Tradition. Es zeigt, welche anderen (als nur die labororientierten) IR-Studien durchgeführt werden können, wobei sich die Betrachtung von frühen Modellen (z.B. Taylor) über Belkins ASK-Konzept bis zu Ingwersens Modell der Polyrepräsentation, und von Bates Berrypicking-Ansatz bis zu Vakkaris "taskbased" IR-Modell erstreckt. Auch Web-IR, OKAPI und Diskussionen zum Relevanzbegriff werden hier thematisiert. - Im folgenden Kapitel schlagen die Autoren ein integriertes IS&R Forschungsmodell vor, bei dem die vielfältigen Beziehungen zwischen Informationssuchenden, Systementwicklern, Oberflächen und anderen beteiligten Aspekten berücksichtigt werden. Ihr Ansatz vereint die traditionelle Laborforschung mit verschiedenen benutzerorientierten Traditionen aus IS&R, insbesondere mit den empirischen Ansätzen zu IS und zum interaktiven IR, in einem holistischen kognitiven Modell. - Kapitel sieben untersucht die Implikationen dieses Modells für IS&R, wobei besonders ins Auge fällt, wie komplex die Anfragen von Informationssuchenden im Vergleich mit der relativen Einfachheit der Algorithmen zum Auffinden relevanter Dokumente sind. Die Abbildung der vielfältig variierenden kognitiven Zustände der Anfragesteller im Rahmen der der Systementwicklung ist sicherlich keine triviale Aufgabe. Wie dabei das Problem der Einbeziehung des zentralen Aspektes der Bedeutung gelöst werden kann, sei dahingestellt. - Im achten Kapitel wird der Versuch unternommen, die zuvor diskutierten Punkte in ein IS&R-Forschungsprogramm (Prozesse - Verhalten - Systemfunktionalität - Performanz) umzusetzen, wobei auch einige kritische Anmerkungen zur bisherigen Forschungspraxis getroffen werden. - Das abschliessende neunte Kapitel fasst das Buch kurz zusammen und kann somit auch als Einstieg in dieThematik gelesen werden. Darauffolgen noch ein sehr nützliches Glossar zu allen wichtigen Begriffen, die in dem Buch Verwendung finden, eine Bibliographie und ein Sachregister. Ingwersen und Järvelin haben hier ein sehr anspruchsvolles und dennoch lesbares Buch vorgelegt. Die gebotenen Übersichtskapitel und Diskussionen sind zwar keine Einführung in die Informationswissenschaft, decken aber einen grossen Teil der heute in dieser Disziplin aktuellen und durch laufende Forschungsaktivitäten und Publikationen berührten Teilbereiche ab. Man könnte es auch - vielleicht ein wenig überspitzt - so formulieren: Was hier thematisiert wird, ist eigentlich die moderne Informationswissenschaft. Der Versuch, die beiden Forschungstraditionen zu vereinen, wird diesem Werk sicherlich einen Platz in der Geschichte der Disziplin sichern. Nicht ganz glücklich erscheint der Titel des Buches. "The Turn" soll eine Wende bedeuten, nämlich jene hin zu einer integrierten Sicht von IS und IR. Das geht vermutlich aus dem Untertitel besser hervor, doch dieser erschien den Autoren wohl zu trocken. Schade, denn "The Turn" gibt es z.B. in unserem Verbundkatalog bereits, allerdings mit dem Zusatz "from the Cold War to a new era; the United States and the Soviet Union 1983-1990". Der Verlag, der abgesehen davon ein gediegenes (wenn auch nicht gerade wohlfeiles) Produkt vorgelegt hat, hätte derlei unscharfe Duplizierend besser verhindert. Ungeachtet dessen empfehle ich dieses wichtige Buch ohne Vorbehalt zur Anschaffung; es sollte in keiner grösseren Bibliothek fehlen."
  10. Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010) 0.00
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    Source
    IEEE Transactions on Visualization and Computer Graphics. InfoVis 2010. [http://systemg.research.ibm.com/apps/facetatlas/cao_infovis10_paper.pdf]
    Year
    2010
  11. Boyack, K.W.; Wylie,B.N.; Davidson, G.S.: Information Visualization, Human-Computer Interaction, and Cognitive Psychology : Domain Visualizations (2002) 0.00
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:17:40
  12. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.00
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    Date
    30. 3.2001 13:32:22
  13. Hancock-Beaulieu, M.: Evaluating the impact of an online library catalogue on subject searching behaviour at the catalogue and at the shelves (1990) 0.00
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    Source
    Journal of documentation. 46(1990), S.318-338
    Year
    1990
  14. Celik, I.; Abel, F.; Siehndel, P.: Adaptive faceted search on Twitter (2011) 0.00
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    Abstract
    In the last few years, Twitter has become a powerful tool for publishing and discussing information. Yet, content exploration in Twitter requires substantial efforts and users often have to scan information streams by hand. In this paper, we approach this problem by means of faceted search. We propose strategies for inferring facets and facet values on Twitter by enriching the semantics of individual Twitter messages and present di erent methods, including personalized and context-adaptive methods, for making faceted search on Twitter more effective.
  15. Vo, D.-T.; Bagheri, E.: Feature-enriched matrix factorization for relation extraction (2019) 0.00
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    Abstract
    Relation extraction aims at finding meaningful relationships between two named entities from within unstructured textual content. In this paper, we define the problem of information extraction as a matrix completion problem where we employ the notion of universal schemas formed as a collection of patterns derived from open information extraction systems as well as additional features derived from grammatical clause patterns and statistical topic models. One of the challenges with earlier work that employ matrix completion methods is that such approaches require a sufficient number of observed relation instances to be able to make predictions. However, in practice there is often insufficient number of explicit evidence supporting each relation type that could be used within the matrix model. Hence, existing work suffer from a low recall. In our work, we extend the work in the state of the art by proposing novel ways of integrating two sets of features, i.e., topic models and grammatical clause structures, for alleviating the low recall problem. More specifically, we propose that it is possible to (1) employ grammatical clause information from textual sentences to serve as an implicit indication of relation type and argument similarity. The basis for this is that it is likely that similar relation types and arguments are observed within similar grammatical structures, and (2) benefit from statistical topic models to determine similarity between relation types and arguments. We employ statistical topic models to determine relation type and argument similarity based on their co-occurrence within the same topics. We have performed extensive experiments based on both gold standard and silver standard datasets. The experiments show that our approach has been able to address the low recall problem in existing methods, by showing an improvement of 21% on recall and 8% on f-measure over the state of the art baseline.
  16. Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011) 0.00
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    Source
    Concepts in context: Proceedings of the Cologne Conference on Interoperability and Semantics in Knowledge Organization July 19th - 20th, 2010. Eds.: F. Boteram, W. Gödert u. J. Hubrich
  17. Liu, X.; Zheng, W.; Fang, H.: ¬An exploration of ranking models and feedback method for related entity finding (2013) 0.00
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    Abstract
    Most existing search engines focus on document retrieval. However, information needs are certainly not limited to finding relevant documents. Instead, a user may want to find relevant entities such as persons and organizations. In this paper, we study the problem of related entity finding. Our goal is to rank entities based on their relevance to a structured query, which specifies an input entity, the type of related entities and the relation between the input and related entities. We first discuss a general probabilistic framework, derive six possible retrieval models to rank the related entities, and then compare these models both analytically and empirically. To further improve performance, we study the problem of feedback in the context of related entity finding. Specifically, we propose a mixture model based feedback method that can utilize the pseudo feedback entities to estimate an enriched model for the relation between the input and related entities. Experimental results over two standard TREC collections show that the derived relation generation model combined with a relation feedback method performs better than other models.
  18. Rekabsaz, N. et al.: Toward optimized multimodal concept indexing (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  19. Kozikowski, P. et al.: Support of part-whole relations in query answering (2016) 0.00
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    Date
    1. 2.2016 18:25:22
  20. Marx, E. et al.: Exploring term networks for semantic search over RDF knowledge graphs (2016) 0.00
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou

Years

Languages

  • e 58
  • d 6
  • chi 1
  • f 1
  • More… Less…

Types

  • a 57
  • el 8
  • m 4
  • r 2
  • x 2
  • s 1
  • More… Less…