Skip to content
Journal article

Web Object Retrieval

Nie Z, Ma Y, Shi S, Wen J, Ma W ...see all

Proceedings of the 16th international conference on World Wide Web (2007) pp. 81--90

  • 80

    Readers

    Mendeley users who have this article in their library.
  • 69

    Citations

    Citations of this article.
  • N/A

    Views

    ScienceDirect users who have downloaded this article.
Sign in to save reference

Abstract

The primary function of current Web search engines is essentially relevance ranking at the document level. However, myriad structured information about real-world objects is embedded in static Web pages and online Web databases. Document-level information retrieval can unfortunately lead to highly inaccurate relevance ranking in answering object-oriented queries. In this paper, we propose a paradigm shift to enable searching at the object level. In traditional information retrieval models, documents are taken as the retrieval units and the content of a document is considered reliable. However, this reliability assumption is no longer valid in the object retrieval context when multiple copies of information about the same object typically exist. These copies may be inconsistent because of diversity of Web site qualities and the limited performance of current information extraction techniques. If we simply combine the noisy and inaccurate attribute information extracted from different sources, we may not be able to achieve satisfactory retrieval performance. In this paper, we propose several language models for Web object retrieval, namely an unstructured object retrieval model, a structured object retrieval model, and a hybrid model with both structured and unstructured retrieval features. We test these models on a paper search engine and compare their performances. We conclude that the hybrid model is the superior by taking into account the extraction errors at varying levels.

Author-supplied keywords

  • information extraction
  • information retrieval
  • language model
  • web objects

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text

Authors

  • Zaiqing Nie

  • Yunxiao Ma

  • Shuming Shi

  • Ji-rong Wen

  • Wei-ying Ma

Cite this document

Choose a citation style from the tabs below