SCIENCE@home

Resource Selection for Federated Search on the Web

Dong Nguyen,T. Demeester,D. Trieschnigg,D. Hiemstra

Published 2016 in arXiv.org

ABSTRACT

A publicly available dataset for federated search reflecting a real web environment has long been absent, making it difficult for researchers to test the validity of their federated search algorithms for the web setting. We present several experiments and analyses on resource selection on the web using a recently released test collection containing the results from more than a hundred real search engines, ranging from large general web search engines such as Google, Bing and Yahoo to small domain-specific engines. First, we experiment with estimating the size of uncooperative search engines on the web using query based sampling and propose a new method using the ClueWeb09 dataset. We find the size estimates to be highly effective in resource selection. Second, we show that an optimized federated search system based on smaller web search engines can be an alternative to a system using large web search engines. Third, we provide an empirical comparison of several popular resource selection methods and find that these methods are not readily suitable for resource selection on the web. Challenges include the sparse resource descriptions and extremely skewed sizes of collections.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    arXiv.org

  • Publication date

    2016-09-01

  • Fields of study

    Computer Science

  • Identifiers
    arXiv 1609.04556
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-25 of 25 references · Page 1 of 1

CITED BY

Showing 1-6 of 6 citing papers · Page 1 of 1