Genre based navigation on the Web

Roussinov, Dmitri; Crowston, Kevin; Nilan, Michael S.; Kwaśnik, Barbara H.; Cai, Jin; Liu, Xiaoyong

doi:10.1109/hicss.2001.926478

Cited by 51 publications

(54 citation statements)

References 12 publications

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“…Roussinov et al [14] view genre as a group of documents with similar form, topic or purpose, "a distinctive type of communicative action, characterized by a socially recognized communicative purpose and common aspects of form". This is a more general view of genre where genre is a grouping of similar documents.…”

Section: Related Workmentioning

confidence: 99%

Learning to classify documents according to genre

Finn

Kushmerick

2006

J. Am. Soc. Inf. Sci.

135

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Current document retrieval tools succeed in locating large numbers of documents relevant to a given query. While search results may be relevant according to the topic of the documents, it is more difficult to identify which of the relevant documents are most suitable for a particular user. Automatic genre analysis -that is, the ability to distinguish documents according to style -would be a useful tool for identifying documents that are most suitable for a particular user. We investigate the use of machine learning for automatic genre classification. We introduce the idea of domain transfer -genre classifiers should be reusable across multiple topics -which doesn't arise in standard text classification. We investigate different features for building genre classifiers and their ability to transfer across multiple topic domains. We also show how different feature-sets can be used in conjunction with each other to improve performance and reduce the number of documents that need to be labeled.

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Section: Related Workmentioning

confidence: 99%

Learning to classify documents according to genre

Finn

Kushmerick

2006

J. Am. Soc. Inf. Sci.

135

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“…Table 1 compiles research that received attention: the table lists the basis of the analysis, the genre palette Q, and the document representation d. The underlying use case is a genre-enabled Web search. The approaches from Crowston and Williams, Roussinov et al, Dimitrova et al were not included since the authors provided suggestions rather than a technical specification about their genre retrieval models [6,29,9].…”

Section: Construction Of Genre Retrieval Modelsmentioning

confidence: 99%

Web Genre Analysis: Use Cases, Retrieval Models, and Implementation Issues

Stein

Eissen

Lipka

2010

Text, Speech and Language Technology

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People who search the World Wide Web often have a multifaceted understanding of their information need: they know what they are searching for, and they know of which form or type the desired documents should be. The former aspect relates to the content of a desired document (= topic), the latter to the presentation of its content and the intended target group. Due to the different user groups and the technical means of the World Wide Web several favorite specializations of Web documents emerged: a document may contain many links (e. g. a link collection), scientific text (e. g. a research article), almost no text but pictures (e. g. an advertisement page), or a short answer to a specific question (e. g. a mail in a help forum). These examples suggest that it can be of much help if the retrieval process is capable to address a user's information need regarding to-what is called here-"genre" or "Web genre". This chapter contributes to Web genre analysis. It presents relevant use cases, discusses existing and new technology for the construction of Web genre retrieval models, and outlines implementation aspects for a genreenabled Web search. Special focus is put on the generalization capability of Web genre retrieval models, for which we present new evaluation measures and, for the first time, a quantitative analysis.

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“…Authors often point out that assigning a genre to a web page might be difficult and controversial (e.g. Roussinov et al, 2001;Meyer zu Eissen and Stein, 2004;Shepherd et al, 2004) because web pages can appear hybrid or peculiar. Genre-mixed web pages or web pages without any evident genre can represent the antecedent of a future genre, but currently they might be considered as belonging to a genre still in formation.…”

Section: Introductionmentioning

confidence: 99%

Implementing a characterization of genre for automatic genre identification of web pages

Santini

Power

Evans

2006

Proceedings of the COLING/ACL on Main Conference Poster Sessions -

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In this paper, we propose an implementable characterization of genre suitable for automatic genre identification of web pages. This characterization is implemented as an inferential model based on a modified version of Bayes' theorem. Such a model can deal with genre hybridism and individualization, two important forces behind genre evolution. Results show that this approach is effective and is worth further research.

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Genre based navigation on the Web

Abstract: We report on our ongoing study of

Cited by 51 publications

References 12 publications

Learning to classify documents according to genre

Learning to classify documents according to genre

Web Genre Analysis: Use Cases, Retrieval Models, and Implementation Issues

Implementing a characterization of genre for automatic genre identification of web pages

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