A method for managing access to web pages: Filtering by Statistical Classification (FSC) applied to text
| Autor: | Eric Nyberg, George T. Duncan, Wenxuan Ding, Ramayya Krishnan, Jonathan P. Caulkins |
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| Rok vydání: | 2006 |
| Předmět: |
Decision support system
Information Systems and Management Information retrieval business.industry Computer science computer.software_genre Management Information Systems Personalization Statistical classification Arts and Humanities (miscellaneous) Content analysis Web page Developmental and Educational Psychology The Internet Web content Data mining business computer Information Systems Content management Block (data storage) |
| Zdroj: | Decision Support Systems. 42:144-161 |
| ISSN: | 0167-9236 |
| DOI: | 10.1016/j.dss.2004.11.015 |
| Popis: | Various entities (e.g., parents, employers) that provide users (e.g., children, employees) access to web content wish to limit the content accessed through those computers. Available filtering methods are crude in that they too often block "acceptable" content while failing to block "unacceptable" content. This paper presents a general and flexible classification method based on statistical techniques applied to text material, that we call, Filtering by Statistical Classification (FSC). According to each individual entity's expressed opinions about what content in a training data set is or is not acceptable, FSC constructs a customized model to represent each individual entity's preferences. FSC then uses this customized model to examine new web content and to block unwanted content. The empirical results suggest that our method has greater predictive power than do a variety of existing approaches. |
| Databáze: | OpenAIRE |
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