Cross-Lingual Linking of News Stories using ESA

In this paper, we describe our approach for Cross-Lingual linking of Indian news stories, submitted for Cross-Lingual Indian News Story Search (CL!NSS) task at FIRE 2012. Our approach consists of two major steps, the reduction of search space by using di�erent features and ranking of the news stories according to their relatedness scores. Our approach uses Wikipedia-based Cross-Lingual Explicit Semantic Analysis (CLESA) to calculate the semantic similarity and relatedness score between two news stories in di�erent languages. We evaluate our approach on CL!NSS dataset, which consists of 50 news stories in English and 50K news stories in Hindi.