A Mean-Variance Analysis Based Approach for Search Result Diversification in Federated Search

作者：Ghansah, Benjamin^*; Wu, Shengli^*

来源：International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 2016, 24(2): 195-211.

DOI：10.1142/S0218488516500100

• Distributed information retrieval
• federated search
• resource selection
• diversification
• mean-variance analysis

Resource Selection is an important step in a federated search environment. The goal of this work was to improve the collection selection process by selecting collections in terms of relevance and diversity, to best answer a user's query. Sampled documents from the Central Sample Database are first ranked by Indri retrieval algorithm and later re-ranked by a Mean-Standard deviation method that reduces uncertainty and improves diversity of collection sources. A comparative evaluation with the R-based diversification metrics shows that the proposed method significantly outperforms the baseline diversification methods; ReDDE+MMR, ReDDE+MAP-IA and state-of-the-art resource selection methods (ReDDE and CORI) in all metrics.

• 出版日期2016-4
• 单位江苏大学