Text condensation as knowledge base abstraction

Reimer, Ulrich; Hahn, Udo

doi:10.1109/caia.1988.196128

Cited by 37 publications

(18 citation statements)

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“…Second, a range is either explicitly given as a range expression of the type [ferml-term2] as with the storage capacity slot of a hard disk frame [see Figure 7 summaries are generated from the text representation structures resulting from the text parse. 26 The structure of WORD EXPERTS is depicted in Figure 3 (this is a simplified form of a notation originally developed by Yonezawa and Hewitt.go Each word expert is characterized by a unique EXPERT-NAME. A word expert becomes active by receiving a message text which may contain some parameters.…”

Section: B An Outline Of the Knowledge Sources Involved In Lexicallymentioning

confidence: 99%

Making understanders out of parsers: Semantically driven parsing as a key concept for realistic text understanding applications

Hahn

1989

Int. J. Intell. Syst.

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Semantically driven natural language parsers have found wide-spread application as a text processing methodology for knowledge-based information retrieval systems. It is argued that this parsing technique particularly corresponds to the requirements inherent to large-scale text analysis. Unfortunately, this approach suffers from several shortcomings which demand a thorough reformulation of its paradigm. Incorporating principles from conceptual analysis and word expert parsing in a model of lexically distributed text parsing, the focus of the modifications proposed in this article, is on a clean declarative separation of linguistic and other knowledge representation levels, abstraction mechanisms leading to a small collection of specification primitives for the parser, and an attempt to incorporate linguistic generalizations and modularization principles into the design of a semantic text grammar. A sample parse illustrates the operation and linguistic coverage of a lexically distributed text parser based on these theoretical considerations with respect to the semantic analysis of noun groups, simple assertional sentences, nominal anaphora, and textual ellipsis.

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Section: B An Outline Of the Knowledge Sources Involved In Lexicallymentioning

confidence: 99%

Making understanders out of parsers: Semantically driven parsing as a key concept for realistic text understanding applications

Hahn

1989

Int. J. Intell. Syst.

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“…Knowledge-based approaches to summarization using a semantic representation of the text were adopted in the SUSY system (Fum, Guida & Tasso, 1985), the SCISOR system (Rau, Jacobs & Zernik, 1989), and the TOPIC system (Hahn & Reimer, 1999;Reimer & Hahn, 1988). The TOPIC system converted the text into a terminological logic representation scheme.…”

Section: Semantic Relations In Automatic Text Summarizationmentioning

confidence: 99%

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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“…In general, the steps adopted to identify domain-specific terms are detecting terminological candidates from texts and selecting the specific entries that can be members of a terminological glossary in the target domain. Different parsing methods ranging from shallow techniques to more sophisticated syntactic approaches are used to identify candidate terms of texts [49,93,163,176].…”

Section: Using Domain-related Key Termsmentioning

confidence: 99%