Context Aware Document Term Weighting for Ad Hoc Search
Bag of words document representations play a fundamental role in modern search engines, but their power is limited by the shallow frequency based term weighting scheme. This paper proposes HDCT, a context aware document term weighting framework for document indexing and retrieval. It first estimates the semantic importance of a term in the context of each passage. These fine grained term weights are then aggregated into a document level bag of words representation, which can be stored into a standard inverted index for efficient retrieval. This paper also proposes two approaches that enable training HDCT without relevance labels. Experiments show that an index using HDCT weights significantly improved the retrieval accuracy compared to typical term frequency and state of the art embedding based indexes.
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