A review on the Detection of Missing Content Queries in FAQ Retrieval Systems
DOI:
https://doi.org/10.24297/ijct.v16i2.5996Keywords:
Frequently Asked Questions, Missing Content QueriesAbstract
When developing an automated FAQ retrieval system, the information supplier constructs question candidates in advance using their own knowledge. Then they answer these question candidates to create question-answer pairs to use in the FAQ retrieval system. However, these question-answer pairs will not always satisfy the users’ information needs. When there is no relevant question–answer pair to a users’ query, such a user may submit various query reformulations browsing over the long results list and may abandon the search before their information need has been satisfied. Such users many never return to use the system again because of the inability of the system to return relevant question-answer pairs to their query. In order to alleviate this, modern automated FAQ retrieval systems use a Missing Content Query (MCQ) detection subsystem to detect those queries that do not have the relevant question–answer pair. In this article we conduct a review of the different approaches proposed in the literature for detecting these MCQs. In particular, we provide a comprehensive review of the different systems that deployed the binary classification approach, the thresholding approach and the hybrid approach in the detection of MCQs. Moreover, we describe the strength and weaknesses of each approach.
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