2006•Unpublished venueRequires access

Identifying User Goals from Web Search Results

Yao-Sheng Chang, Kuan-Yu He, Scott Yu, Wen‐Hsiang Lu

Open publisher page 17 citations

Abstract

With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to reduce overloaded information by understanding user goals clearly. In this paper, we intend to utilize Web search results to identify user goals. We propose one novel probabilistic inference model which effectively employs syntactic features to discover a variety of confined user goals

About this research paper

What this paper is about

With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to reduce overloaded information by understanding user goals clearly. In this paper, we intend to utilize Web search results to identify user goals. We propose one novel probabilistic inference model which effectively employs syntactic features to discover a variety of confined user goals

Why it matters

OpenAlex reports 17 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Available abstract

With the fast growth of the Web, users often suffer from the problem of information overload since many existing search engines response lots of non-relevant documents containing query terms based on the search mechanism of keyword matching. In fact, it is eagerly expected by both users and search engine developers to reduce overloaded information by understanding user goals clearly. In this paper, we intend to utilize Web search results to identify user goals. We propose one novel probabilistic inference model which effectively employs syntactic features to discover a variety of confined user goals

Key concepts: Computer science, Search engine, Variety (cybernetics), Web search query, Information retrieval, World Wide Web, Inference, Information overload

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