Collaborative Ranking: A Case Study on Entity Linking

In this paper, we present a new ranking scheme, collaborative ranking (CR). In contrast to traditional non-collaborative ranking scheme which solely relies on the strengths of isolated queries and one stand-alone ranking algorithm, the new scheme integrates the strengths from multiple collaborators of a query and the strengths from multiple ranking algorithms. We elaborate three specific forms of collaborative ranking, namely, micro collaborative ranking (MiCR), macro collaborative ranking (MaCR) and micro-macro collaborative ranking (MiMaCR). Experiments on entity linking task show that our proposed scheme is indeed effective and promising.

• Type: Journal
• Year: 2011
• Where: EMNLP
• Authors: Zheng Chen, Heng Ji
• Keywords: Collaborators, EMNLP 2011, Macr, Natural Language Processing, Speci