Knowledge retrieval is a long standing problem that faces the challenge of dealing with natural language data. Such data is produced and consumed by humans and therefore is ambiguous and unstructured by nature. Recent studies focused on using unstructured data as sources for answers, with interesting results. We used Stack Overflow public data and searched for answers in external sources. Results showed that this approach is feasible. Furthermore, we explored machine-learned models and were able to improve the baseline results by leveraging the tag information predicted from new questions.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Knowledge retrieval is a long standing problem that faces the challenge of dealing with natural language data. Such data is produced and consumed by humans and therefore is ambiguous and unstructured by nature. Recent studies focused on using unstructured data as sources for answers, with interesting results. We used Stack Overflow public data and searched for answers in external sources. Results showed that this approach is feasible. Furthermore, we explored machine-learned models and were able to improve the baseline results by leveraging the tag information predicted from new questions. 76 pp. Englisch. Codice articolo 9783659914331
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Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Knowledge retrieval is a long standing problem that faces the challenge of dealing with natural language data. Such data is produced and consumed by humans and therefore is ambiguous and unstructured by nature. Recent studies focused on using unstructured data as sources for answers, with interesting results. We used Stack Overflow public data and searched for answers in external sources. Results showed that this approach is feasible. Furthermore, we explored machine-learned models and were able to improve the baseline results by leveraging the tag information predicted from new questions. Codice articolo 9783659914331
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 76 pages. 8.66x5.91x0.18 inches. In Stock. Codice articolo 3659914339
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Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Lima EduardoEduardo Lima graduated as B.S. in Computer Engineering by UFRN, RN, Brazil in 2003. Since 2003, had lectured in IT Vocational Schools in Natal, Brazil. In 2013, started to teach in IFRN, RN, Brazil. In 2015, founded the R. Codice articolo 158125260
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Knowledge retrieval is a long standing problem that faces the challenge of dealing with natural language data. Such data is produced and consumed by humans and therefore is ambiguous and unstructured by nature. Recent studies focused on using unstructured data as sources for answers, with interesting results. We used Stack Overflow public data and searched for answers in external sources. Results showed that this approach is feasible. Furthermore, we explored machine-learned models and were able to improve the baseline results by leveraging the tag information predicted from new questions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. Codice articolo 9783659914331
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Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Mining Unstructured Knowledge Bases for Question & Answers Websites | A Case Study of Stack Overflow | Eduardo Lima | Taschenbuch | 76 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659914331 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 103458117
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