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Abstract

State of the art review of natural language processing updating an earlier review published in ARIST 22(1987). Discusses important developments that have allowed for significant advances in the field of natural language processing: materials and resources; knowledge based systems and statistical approaches; and a strong emphasis on evaluation. Reviews some natural language processing applications and common problems still awaiting solution. Considers closely related applications such as language generation and th egeneration phase of machine translation which face the same problems as natural language processing. Covers natural language methodologies for information retrieval only briefly

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Source

ACM transactions on information systems. 7(1989) no.3, S.292-316

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Abstract

The use of terms from natural and social science titles and abstracts is studied from the perspective of sublanguages and their specialized dictionaries. Explores different notions of sublanguage distinctiveness. Object methods for separating hard and soft sciences are suggested based on measures of sublanguage use, dictionary characteristics, and sublanguage distinctiveness. Abstracts were automatically classified with a high degree of accuracy by using a formula that condsiders the degree of uniqueness of terms in each sublanguage. This may prove useful for text filtering of information retrieval systems

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Abstract

A text window is a group of words appearing in contiguous positions in text used to exploit a variety of lexical, syntactics, and semantic relationships without having to analyze the text explicitely for their structure. This supports the previously suggested idea that natural grouping of words are best treated as a unit of size 7 to 11 words, that is, plus or minus 3 to 5 words. The text retrieval experiments varying the size of windows, both with full text and with stopwords removed, support these size ranges. The characteristcs of windows that best match terms in queries are examined in detail, revealing intersting differences between those for queries with good results and those for queries with poorer results. Queries with good results tend to contain morte content word phrase and few terms with high frequency of use in the database. Information retrieval systems may benefit from expanding thesaurus-style relationships or incorporating statistical dependencies for terms within these windows

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Abstract

Previous research describing Web page and link classification systems resulting from a content analysis of over 75 Web pages left us with four unanswered questions: (1) What is the most useful apllication of page types: as descriptions of entire pages or as components that are combined to create pages? (2) Is there a kind of analysis that we can perform on isolated anchors, which can be text, icons, or both together, that is equivalent to the syntactic analysis for embedded and labeld anchors? (3) How explicitly are readers informed about what can be found by traversing a link, especially for the relatively broad categories of expansion and resource links? (4) Is there a relationship between the type of link and whther its target is a whole page or a fragment, or of its target is in the same site or a different site than its source? This article examines these questions