Building a Lexicon from Machine-Readable Dictionaries for Improved Information Retrieval

Nutter, J. Terry; Fox, Edward A.; Evens, Martha

doi:10.1093/llc/5.2.129

Cited by 18 publications

(6 citation statements)

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“…Based on the substantial work on lexicography and ontology [19,12,25,14,15], four primitive relationships between atomic concepts are considered in our current study. They are Is-A, Part-Whole, Synonym, and Antonym, each of which is denoted using a binary predicate.…”

Section: Concept Relationsmentioning

confidence: 99%

“…To reflect cognitive relations among the concepts as expressed by or embodied in words in natural languages, the theory of lexical relations was developed [19], where information is represented as a collection of nodes connected by labeled arcs that express links or relationships between the nodes. These links may represent semantic and syntactic relationships among concepts, and can be used to reflect not only major aspects of word meaning, but also their morphological relationships [25]. The most widely recognized relationships include is-a, part-whole, synonym, antonym, which can be denoted using either a labeled arc or a proposition node.…”

Section: Related Workmentioning

confidence: 99%

“…A hierarchy of lexical-semantic relations is thus constructed which contains both basic and non-basic semantic relations as well as a large number of lexical relations. Many (but not all) of the lexical relations so far identified can be extracted automatically from dictionary definitions [25]. CYC developed in [21] aims to build a common sense knowledge base consisting of roughly 100,000 general concepts spanning all aspects of human reality.…”

Section: Related Workmentioning

confidence: 99%

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Beyond information searching and browsing: acquiring knowledge from digital libraries

Feng

Jeusfeld

Hoppenbrouwers

2005

Information Processing & Management

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As one of the most complex and advanced forms of Internet information systems, digital libraries serve as an increasingly important channel to a vast array of information sources and services. However, from the standpoint of satisfying human's information needs, the current digital library systems suffer from the following two shortcomings: (i) inadequate strategic level cognition support; (ii) inadequate knowledge sharing facilities. In this paper, we introduce a two-layered digital library architecture to support different levels of human cognitive acts. The model moves beyond simple information searching and browsing across multiple repositories, to inquiry of knowledge. To address users' high-order cognitive requests, we propose an information space, consisting of a knowledge subspace and a document subspace. A formal description of the knowledge subspace for knowledge sharing and dissemination, as well as mechanisms for constructing the two subspaces, are particularly discussed. Such an enhanced information space extends the traditional role of digital libraries as information provider to information & knowledge provider. Some distinguished features in comparison with the traditional knowledge-based systems are also discussed in the paper. are there any important features missing from the current DL systems? To answer these questions, let's first look at a scenario on the use of a DL system.Kooper works in a city plan & management office. He is investigating the precaution policy against flood this year. If there will be a flood in the coming summer, necessary actions (e.g., strengthing the embankment, resource allocation, etc.) must be taken now to prevent the city from sustaining losses. According to Kooper's previous experience, it seems that "A wet winter might cause flood in summer." To confirm this pre-conceived hypothesis, he logins on a DL system to request information talking about the reasons of flood. The DL system returns a number of articles. He browses through the returned article list and selects three articles that look most relevant. All of the three articles mention that "A precursor to the flooding in summer is a wet winter." To assure this information is also valid for the area where Kooper lives, he accesses the DL again to ask for documents reporting river flood in the city before. From the articles returned, he gets to know the latest 3 severe flood that happened in 1986, 1995, 1997, respectively, in the city. He then navigates to the meteorological repository of the DL, and accesses the weather information of the city during the winter time of these three years. He notes a tight correlation between wet winter and flood summer. Based on the information obtained from the DL, Kooper is pretty sure now about his prior flood prediction assumption for the city. He logs off the system. Having experienced a very wet winter this year, Kooper decides to draw up a city flood precaution plan immediately.From this scenario, we observe that a number of deficiencies exist in current DL systems. Bel...

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Section: Concept Relationsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Beyond information searching and browsing: acquiring knowledge from digital libraries

Feng

Jeusfeld

Hoppenbrouwers

2005

Information Processing & Management

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“…Building upon earlier work with "intelligent" information retrieval in connection with the CODER (COmposite Document Expert]extended/effective Retrieval) system [FOX87], we observed the value of having the contents of machine readable dictionaries in an easy to manipulate computer form [FOX88a]. A large lexicon of this type should be useful to aid information retrieval by allowing automatic and semi-automatic query expansion [NUTT89]. Further, it should support a range of text understanding and other natural language proceasing activities [FRAN89].…”

Section: Sources Of Static Key Setsmentioning

confidence: 88%

Order preserving minimal perfect hash functions and information retrieval

Fox

Chen

Daoud

et al. 1989

Proceedings of the 13th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

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Rapid access to information is essential for a wide variety of retrieval systems and applications. Hashing has long been used when the fastest possible direct search is desired, but is generally not appropriate when sequential or range searches are also required. This paper describes a hashing method, developed for collections that are relatively static, that supports both direct and sequential access. Indeed, the algorithm described gives hash functions that are optimal in terms of time and hash table space utilization, and that preserve any a priori ordering desired. Furthermore, the resulting order preserving minimal perfect hash functions (OPMPHFs) can be found using space and time that is on average linear in the number of keys involved.

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“…Entity concepts are used to describe concept terms, while relation concepts are mainly for presenting various relationships among concept terms. Based on the substantial work on lexicography and ontology [19,12,8,14,10,11], three typical primitive relationships (Is-A, Synonym, and Opposite) between concepts can be established.…”

Section: Conceptsmentioning

confidence: 99%

A Strategic Level for Scientific Digital Libraries

Feng

Jeusfeld

Hoppenbrouwers

2002

Lecture Notes in Computer Science

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Building a Lexicon from Machine-Readable Dictionaries for Improved Information Retrieval

Cited by 18 publications

References 0 publications

Beyond information searching and browsing: acquiring knowledge from digital libraries

Beyond information searching and browsing: acquiring knowledge from digital libraries

Order preserving minimal perfect hash functions and information retrieval

A Strategic Level for Scientific Digital Libraries

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