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Matching sets of parse trees for answering multi-sentence questions
The problem of answering multi-sentence questions is addressed in a number of products and services-related domains. A candidate set of answers, obtained by a keyword search, is re-ranked by matching the set of parse trees of an answer with that of the question. To do that, a graph representation and learning technique for parse structures for paragraphs of text have been developed. Parse Thicket (PT) as a set of syntactic parse trees augmented by a number of arcs for inter-sentence word-word relations such as coreference and taxonomic relations is introduced. These arcs are also derived from other sources, including Speech Act and Rhetoric Structure theories. The proposed approach is subject to evaluation in the product search and recommendation domain, where search queries include multiple sentences. An open source plugin for SOLR is developed so that the proposed technology can be easily integrated with industrial search engines.