Exploiting Thread Structures to Improve Smoothing of Language Models for Forum Post Retrieval

作者: Huizhong Duan , Chengxiang Zhai

DOI: 10.1007/978-3-642-20161-5_35

关键词:

摘要: Due to many unique characteristics of forum data, post retrieval is different from traditional document and web search, raising interesting research questions about how optimize the accuracy retrieval. In this paper, we study exploit naturally available raw thread structures forums improve in language modeling framework. Specifically, propose two schemes for smoothing model a based on containing post. We explore several variants ways. also create human annotated test data set evaluate proposed methods using set. The experiment results show that leveraging threads estimation models are effective, they outperform existing task.

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