Difference between revisions of "Wikipedia-Based Semantic Interpretation for Natural Language Processing"

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== Overview ==
 
== Overview ==
 
Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was based on purely statistical techniques that did not make use of background knowledge, on limited lexicographic knowledge bases such as [[WordNet]], or on huge manual efforts such as the CYC project. Here authors propose a novel method, called Explicit Semantic Analysis (ESA), for fine-grained semantic interpretation of unrestricted natural language texts. Authors method represents meaning in a high-dimensional space of concepts derived from [[Wikipedia]], the largest encyclopedia in existence. Authors explicitly represent the meaning of any text in terms of Wikipedia-based concepts. Authors evaluate the effectiveness of method on text categorization and on computing the degree of semantic [[relatedness]] between fragments of natural language text. Using ESA results in significant improvements over the previous state of the art in both tasks. Importantly, due to the use of natural concepts, the ESA model is easy to explain to human users.
 
Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was based on purely statistical techniques that did not make use of background knowledge, on limited lexicographic knowledge bases such as [[WordNet]], or on huge manual efforts such as the CYC project. Here authors propose a novel method, called Explicit Semantic Analysis (ESA), for fine-grained semantic interpretation of unrestricted natural language texts. Authors method represents meaning in a high-dimensional space of concepts derived from [[Wikipedia]], the largest encyclopedia in existence. Authors explicitly represent the meaning of any text in terms of Wikipedia-based concepts. Authors evaluate the effectiveness of method on text categorization and on computing the degree of semantic [[relatedness]] between fragments of natural language text. Using ESA results in significant improvements over the previous state of the art in both tasks. Importantly, due to the use of natural concepts, the ESA model is easy to explain to human users.
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=== Wikipedia Quality ===
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Gabrilovich, Evgeniy; Markovitch, Shaul. (2009). "[[Wikipedia-Based Semantic Interpretation for Natural Language Processing]]". AI Access Foundation. DOI: 10.1613/jair.2669.
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=== English Wikipedia ===
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{{cite journal |last1=Gabrilovich |first1=Evgeniy |last2=Markovitch |first2=Shaul |title=Wikipedia-Based Semantic Interpretation for Natural Language Processing |date=2009 |doi=10.1613/jair.2669 |url=https://wikipediaquality.com/wiki/Wikipedia-Based_Semantic_Interpretation_for_Natural_Language_Processing |journal=AI Access Foundation}}
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=== HTML ===
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Gabrilovich, Evgeniy; Markovitch, Shaul. (2009). &amp;quot;<a href="https://wikipediaquality.com/wiki/Wikipedia-Based_Semantic_Interpretation_for_Natural_Language_Processing">Wikipedia-Based Semantic Interpretation for Natural Language Processing</a>&amp;quot;. AI Access Foundation. DOI: 10.1613/jair.2669.
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Revision as of 09:04, 22 February 2021


Wikipedia-Based Semantic Interpretation for Natural Language Processing
Authors
Evgeniy Gabrilovich
Shaul Markovitch
Publication date
2009
DOI
10.1613/jair.2669
Links
Original Preprint

Wikipedia-Based Semantic Interpretation for Natural Language Processing - scientific work related to Wikipedia quality published in 2009, written by Evgeniy Gabrilovich and Shaul Markovitch.

Overview

Adequate representation of natural language semantics requires access to vast amounts of common sense and domain-specific world knowledge. Prior work in the field was based on purely statistical techniques that did not make use of background knowledge, on limited lexicographic knowledge bases such as WordNet, or on huge manual efforts such as the CYC project. Here authors propose a novel method, called Explicit Semantic Analysis (ESA), for fine-grained semantic interpretation of unrestricted natural language texts. Authors method represents meaning in a high-dimensional space of concepts derived from Wikipedia, the largest encyclopedia in existence. Authors explicitly represent the meaning of any text in terms of Wikipedia-based concepts. Authors evaluate the effectiveness of method on text categorization and on computing the degree of semantic relatedness between fragments of natural language text. Using ESA results in significant improvements over the previous state of the art in both tasks. Importantly, due to the use of natural concepts, the ESA model is easy to explain to human users.

Embed

Wikipedia Quality

Gabrilovich, Evgeniy; Markovitch, Shaul. (2009). "[[Wikipedia-Based Semantic Interpretation for Natural Language Processing]]". AI Access Foundation. DOI: 10.1613/jair.2669.

English Wikipedia

{{cite journal |last1=Gabrilovich |first1=Evgeniy |last2=Markovitch |first2=Shaul |title=Wikipedia-Based Semantic Interpretation for Natural Language Processing |date=2009 |doi=10.1613/jair.2669 |url=https://wikipediaquality.com/wiki/Wikipedia-Based_Semantic_Interpretation_for_Natural_Language_Processing |journal=AI Access Foundation}}

HTML

Gabrilovich, Evgeniy; Markovitch, Shaul. (2009). &quot;<a href="https://wikipediaquality.com/wiki/Wikipedia-Based_Semantic_Interpretation_for_Natural_Language_Processing">Wikipedia-Based Semantic Interpretation for Natural Language Processing</a>&quot;. AI Access Foundation. DOI: 10.1613/jair.2669.