Fine-grained topic detection in news search results

  • Authors:
  • Jia Cheng;Jingyu Zhou;Shuang Qiu

  • Affiliations:
  • Shanghai Jiao Tong University, Shanghai, P. R. China;Shanghai Jiao Tong University, Shanghai, P. R. China;Shanghai Jiao Tong University, Shanghai, P. R. China

  • Venue:
  • Proceedings of the 27th Annual ACM Symposium on Applied Computing
  • Year:
  • 2012

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Abstract

Current news search engines return results in many clusters, but often not very accurate. This paper studies fine-grained topic detection within news search results, which faces the challenges of short result length and highly related content. We propose an agglomerative clustering algorithm with a novel combination of similarity measures and use simulated annealing for optimization. Experimental results demonstrate that our approach can significantly outperform original search engine results.