2015, ISBN: 3668109222

[EAN: 9783668109223], Neubuch, [PU: GRIN Verlag Dez 2015], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, This item is printed on demand … Mehr…

[EAN: 9783668109223], Neubuch, [PU: GRIN Verlag Dez 2015], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, This item is printed on demand - it takes 3-4 days longer - Neuware -Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - Miscellaneous, , course: Graduate Program in Computer Science, language: English, abstract: The Open Information Extraction (Open IE) is a relation extraction paradigm in which the target relationships cannot be specified in advance, and it aims to overcome the limitations imposed by traditional IE methods, such as domain-dependence and scalability.In order to extend Open IE to extract relationships that are not expressed by verbs from texts in English, we introduce CompIE, a component that learns relations expressed in noun compounds (NCs), such as (oil, extracted from, olive) from olive oil, or in adjective-noun pairs (ANs), such as (moon, that is, gorgeous) from gorgeous moon. CompIE input is a text file, and the output is a set of triples describing binary relationships. The architecture comprises two main tasks: NCs and ANs Extraction (1) and NCs and ANs Interpretation (2). The first task generates a list of NCs and ANs from the input corpus. The second task performs the interpretation of NCs and ANs and generates the tuples that describe the relations extracted from the corpus. In order to study CompIE's feasibility, we perform an evaluation based on hypotheses. In order to implement the strategies to validate each hypothesis we have built a prototype. The results show that our solution achieves 89% Precision and demonstrate that CompIE reaches its goal of extending Open IE paradigm extracting relationships within NCs and ANs. 224 pp. Englisch, Books<

2015, ISBN: 3668109222

[EAN: 9783668109223], Neubuch, [SC: 0.0], [PU: GRIN Verlag], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, Druck auf Anfrage Neuware - P… Mehr…

[EAN: 9783668109223], Neubuch, [SC: 0.0], [PU: GRIN Verlag], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, Druck auf Anfrage Neuware - Printed after ordering - Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - Miscellaneous, , course: Graduate Program in Computer Science, language: English, abstract: The Open Information Extraction (Open IE) is a relation extraction paradigm in which the target relationships cannot be specified in advance, and it aims to overcome the limitations imposed by traditional IE methods, such as domain-dependence and scalability.In order to extend Open IE to extract relationships that are not expressed by verbs from texts in English, we introduce CompIE, a component that learns relations expressed in noun compounds (NCs), such as (oil, extracted from, olive) from olive oil, or in adjective-noun pairs (ANs), such as (moon, that is, gorgeous) from gorgeous moon. CompIE input is a text file, and the output is a set of triples describing binary relationships. The architecture comprises two main tasks: NCs and ANs Extraction (1) and NCs and ANs Interpretation (2). The first task generates a list of NCs and ANs from the input corpus. The second task performs the interpretation of NCs and ANs and generates the tuples that describe the relations extracted from the corpus. In order to study CompIE's feasibility, we perform an evaluation based on hypotheses. In order to implement the strategies to validate each hypothesis we have built a prototype. The results show that our solution achieves 89% Precision and demonstrate that CompIE reaches its goal of extending Open IE paradigm extracting relationships within NCs and ANs. 224 pp. Englisch, Books<

2015, ISBN: 3668109222

[EAN: 9783668109223], Neubuch, [SC: 0.0], [PU: GRIN Verlag], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, Druck auf Anfrage Neuware - P… Mehr…

[EAN: 9783668109223], Neubuch, [SC: 0.0], [PU: GRIN Verlag], INFORMATIONEXTRACTION; NATURALLANGUAGEPROCESSING; OPENINFORMATIONEXTRACTION; RELATIONEXTRACTION, Druck auf Anfrage Neuware - Printed after ordering - Doctoral Thesis / Dissertation from the year 2014 in the subject Computer Science - Miscellaneous, , course: Graduate Program in Computer Science, language: English, abstract: The Open Information Extraction (Open IE) is a relation extraction paradigm in which the target relationships cannot be specified in advance, and it aims to overcome the limitations imposed by traditional IE methods, such as domain-dependence and scalability.In order to extend Open IE to extract relationships that are not expressed by verbs from texts in English, we introduce CompIE, a component that learns relations expressed in noun compounds (NCs), such as (oil, extracted from, olive) from olive oil, or in adjective-noun pairs (ANs), such as (moon, that is, gorgeous) from gorgeous moon. CompIE input is a text file, and the output is a set of triples describing binary relationships. The architecture comprises two main tasks: NCs and ANs Extraction (1) and NCs and ANs Interpretation (2). The first task generates a list of NCs and ANs from the input corpus. The second task performs the interpretation of NCs and ANs and generates the tuples that describe the relations extracted from the corpus. In order to study CompIE's feasibility, we perform an evaluation based on hypotheses. In order to implement the strategies to validate each hypothesis we have built a prototype. The results show that our solution achieves 89% Precision and demonstrate that CompIE reaches its goal of extending Open IE paradigm extracting relationships within NCs and ANs., Books<

2015, ISBN: 9783668109223

Taschenbuch

GRIN Verlag, Taschenbuch, Auflage: 1. 224 Seiten, Publiziert: 2015-12-14T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 9783668109223, 0.3 kg, Computer & Internet, Kategorien, Bücher, In… Mehr…

GRIN Verlag, Taschenbuch, Auflage: 1. 224 Seiten, Publiziert: 2015-12-14T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 9783668109223, 0.3 kg, Computer & Internet, Kategorien, Bücher, Ingenieurwissenschaft & Technik, Naturwissenschaften & Technik, Fremdsprachige Bücher, Featured Categories, Englische Bücher, 7c9a6c79-19ea-4dea-90da-d7d47042d341_2301, 7c9a6c79-19ea-4dea-90da-d7d47042d341_0, Arborist Merchandising Root, acc906d0-2585-4921-a56f-3ff277850936_4901, acc906d0-2585-4921-a56f-3ff277850936_0, Special Features Stores, Taschenbücher, acc906d0-2585-4921-a56f-3ff277850936_4201, GRIN Verlag, 2015<

ISBN: 9783668109223

*Learning Non-Verbal Relations Under Open Information Extraction Paradigm* - 1. Auflage / Taschenbuch für 52.95 € / Aus dem Bereich: Bücher, Ratgeber, Computer & Internet Medien > Bücher … Mehr…

*Learning Non-Verbal Relations Under Open Information Extraction Paradigm* - 1. Auflage / Taschenbuch für 52.95 € / Aus dem Bereich: Bücher, Ratgeber, Computer & Internet Medien > Bücher nein Buch (kartoniert) Hardcover;Naturwissenschaften, Medizin, Informatik, Technik;Sonstiges, GRIN Verlag<