Answering Complex Queries in an Online Community Network

Authors

  • Azade Nazi University of Texas at Arlington
  • Saravanan Thirumuruganathan University of Texas at Arlington
  • Vagelis Hristidis University of California, Riverside
  • Nan Zhang George Washington University
  • Gautam Das University of Texas at Arlington

DOI:

https://doi.org/10.1609/icwsm.v9i1.14671

Keywords:

online community network, complex queries, access model, heterogeneous graph

Abstract

An online community network such as Twitter or amazon.com links entities (e.g., users, products) with various relationships (e.g., friendship, co-purchase) and make such information available for access through a web interface. The web interfaces of these networks often support features such as keyword search and "get-neighbors" — so a visitor can quickly find entities (e.g., users/products) of interest. Nonetheless, the interface is usually too restrictive to answer complex queries such as (1) find 100 Twitter users from California with at least 100 followers who talked about ICWSM last year or (2) find 100 books with at least 200 5-star reviews at amazon.com. In this paper, we introduce the novel problem of answering complex queries that involve non-searchable attributes through the web interface of an online community network. We model such a network as a heterogeneous graph with two access channels, Content Search and Local Search. We propose a unified approach that transforms the complex query into a small number of supported ones based on a strategic query-selection process. We conduct comprehensive experiments on Twitter and amazon.com which demonstrate the efficacy of our proposed algorithms.

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Published

2021-08-03

How to Cite

Nazi, A., Thirumuruganathan, S., Hristidis, V., Zhang, N., & Das, G. (2021). Answering Complex Queries in an Online Community Network. Proceedings of the International AAAI Conference on Web and Social Media, 9(1), 662-665. https://doi.org/10.1609/icwsm.v9i1.14671