Structured-information extraction from patent-claim sentences

Nishida, Fujio; Takamatsu, Shinobu

doi:10.1016/0306-4573(82)90046-2

Cited by 15 publications

(5 citation statements)

References 3 publications

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“…In the 1980s and early 1990s, some researchers developed conceptual information retrieval systems that made use of complex linguistic processing and knowledge‐based inferencing to extract information from text to store in a semantic representation or knowledge representation system. Examples of such systems are RIME (Berrut, 1990), the patent‐claim retrieval system described by Nishida and Takamatsu (1982), SCISOR (Rau, 1987; Rau et al, 1989), and FERRET (Mauldin, 1991). Information retrieval was performed by comparing the information in the store with the semantic representation of the user's query.…”

Section: Semantic Relations In Information Retrievalmentioning

confidence: 99%

“…Examples of such systems are the RIME system (Berrut, 1990), the patent-claim retrieval system described by Nishida & Takamatsu (1982), the SCISOR system (Rau, 1987;Rau, Jacobs & Zernik, 1989), and the FERRET system (Mauldin, 1991). Information retrieval was performed by comparing the information in the store with the semantic representation of the user's query.…”

Section: Relation Matching For Precision Enhancementmentioning

confidence: 99%

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Semantic relations in information science

Khoo

2006

Annual Review Info Sci & Tec

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Abstract. This chapter examines the nature of semantic relations and their main applications in information science. The nature and types of semantic relations are discussed from the perspectives of linguistics and psychology. An overview of the semantic relations used in knowledge structures such as thesauri and ontologies are provided, as well as the main techniques used in the automatic extraction of semantic relations from text. The chapter then reviews the use of semantic relations in information extraction, information retrieval, question-answering and automatic text summarization applications.

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Section: Semantic Relations In Information Retrievalmentioning

confidence: 99%

Section: Relation Matching For Precision Enhancementmentioning

confidence: 99%

Semantic relations in information science

Khoo

2006

Annual Review Info Sci & Tec

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“…Four examples of conceptual information retrieval systems are the RIME system (Berrut, 1990), the patent-claim retrieval system described by Nishida and Takamatsu (1982), the SCISOR system (Rau, 1987;Rau, Jacobs & Zernik, 1989) and the FERRET system (Mauldin, 1991). The RIME system was used for retrieving X-ray pictures associated with a medical report describing in natural language the content and medical interpretation of the picture.…”

Section: Use Of Semantic Relationsmentioning

confidence: 99%

“…The system automatically converted the medical reports to binary tree structures that represented medical concepts and relations between them. The patent-claim retrieval system described by Nishida and Takamatsu (1982) extracted information from patent-claim sentences in patent documents and stored the information in a relational database. The SCISOR system extracted information from short newspaper stories in the domain of corporate takeovers, and stored the information in the "KODIAK" knowledge representation.…”

Section: Use Of Semantic Relationsmentioning

confidence: 99%

The use of relation matching in information retrieval

Khoo¹

1997

LIBRES

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Most information retrieval systems use keywordmatching to identify documents that may be relevant to the user's query. The user's query may contain multiple concepts linked together with relations. However, keyword matching methods ignore relations that are expressed in the query. This paper discusses the use of relation matching in information retrievalmatching terms and relations between terms expressed in the query with terms and relations found in the documents. Previous studies on relation matching are surveyed, and related issues and problems are discussed. The results of research carried out as part of the author's dissertation are reported and current research efforts are outlined. This document may be circulated freely with the following statement included in its entirety:

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“…1,2 Subsequently, structural analysis of text has been introduced. [5][6][7][8][9][10][11] It is based on the concept of case and frame presented by Fillmore and Minsky3,4 and aimes at processing of structured information or knowledge involved in text. Extacting, storing, and handling of structured information will be essential to knowledge engineering and information science in the near future.…”

Section: Introductionmentioning

confidence: 99%