Integrate Multilingual Web Search Results using Cross-Lingual Topic Models
Duo Ding · 2011
With the thriving of the Internet, web users today have access to resources around the world in more than 200 different languages. How to effectively manage multilingual web search results has emerged as an essential problem. In this paper, we introduce the ongoing work of leveraging a Cross-Lingual Topic Model (CLTM) to integrate the multilingual search results. The CLTM detects the underlying topics of different language results and uses the topic distribution of each result to cluster them into topic-based classes. In CLTM, we unify distributions in topic level by direct translation, thus distinguishing from other multilingual topic models, which mainly concern the parallelism at document or sentence level (Mimno 2009; Ni, 2009). Experimental results suggest that our CLTM clustering method is effective and outperforms the 6 compared clustering approaches. 1