Query-Topic Focused Web Pages Summarization
نویسندگان
چکیده
We present a novel Web Pages Summarizer ContextSummarizer that subgroups the given Web pages into ‘sense-clusters’ respecting a user’s topic interests, and constructs a dynamic extractive summary for each sense-cluster. A user’s topic interest is described by the user who selects and refines some of word senses disambiguated within the content contexts of the given Web pages. The semantic similarity measures between the contents of Web pages/segments/sentences and the user-selected/-refined word senses were used to choose the most topically relevant sentences as the extractive summaries referring to a user’s topic interest. As the results, it addressed the dynamic semanticalignment issues between the content of a Web page and the user’s topic interest about that Web page, and between the user’s topic interest and an extractive summary. Some case studies and experimental results showed that query-topic focused extractive summaries returns more topically consistent sentences for an extractive summary.
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