Finding similar questions in large question and answer archives

By Jiwoon Jeon, W. Bruce Croft, Joon Ho Lee. International Conference on Information and Knowledge Management, 2005

480 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/78e94a44b8fd26ac6509176a1c706441c3376668

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Citations in the corpus

Improving bug localization using structured information retrieval (2013, background): “In fact, the idea that the same documents should be relevant for similar queries provides the foundation for search community question and answer forums today [16].”
Retrieval models for question and answer archives (2008, background): “In section 2, we reviewed some previous attempts [6, 10, 8] to address these problems.”
SemEval-2016 Task 3: Community Question Answering (2019, methodology): “…are normally applied to pairs of questions and answer passages to derive a relative order between passages, e.g., see (Radlin-ski and Joachims, 2005; Jeon et al., 2005; Shen and Lapata, 2007; Moschitti et al., 2007; Severyn and Moschitti, 2015; Moschitti, 2008; Tymoshenko and Moschitti, 2015;…”
Finding the right facts in the crowd: factoid question answering over social media (2008, methodology): “[10] presented retrieval methods based on machine translation models to find similar questions from Naver, a community QA service, but did not take quality of answers into consideration.”
Latent Semantic Tensor Indexing for Community-based Question Answering (2013, methodology): “Jeon et al. (2005a; 2005b) compared four diﬀerent retrieval methods, i.e., the vector space model(Jijkoun and de Rijke, 2005), the Okapi BM25 model (Robertson et al., 1994), the language model, and the translation model, for question retrieval on CQA data, and the experimental results showed that…”
Learning Continuous Word Embedding with Metadata for Question Retrieval in Community Question Answering (2015, methodology): “Jeon et al. (2005) proposed a wordbased translation model for automatically fixing the lexical gap problem.”
Clickthrough-based translation models for web search: from word models to phrase models (2010, background): “This problem has also been studied in [36, 20, 24, 21].”
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks (2015, background): “For example, [17, 24] designed classiﬁers of question and answer passage pairs.”
Modelling input texts: from Tree Kernels to Deep Learning (2015, methodology): “Passage reranking using classifiers of question and answer pairs were proposed in [62,120].”
Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs (2020, background): “The problem of matching general unanswered questions with semantically similar answered questions has been well-studied in the context of online user forums [7, 9, 11, 27], community QA [8, 16, 29] and question answer archives [15, 16].”
A question-entailment approach to question answering (2019, background): “[40] showed that a retrieval model based on translation probabilities, learned from a question and answer archive, can recognize semantically similar questions.”
A framework to predict the quality of answers with non-textual features (2006, methodology): “The 125 queries are used and the question part of the Q&A pair is searched to find relevant Q&A pairs to the query, because the question part is known to be much more useful than the answer part in finding relevant Q&A pairs [8, 6].”
Entity based Q&A Retrieval (2012, methodology): “Translation based language models: TLM (Jeon et al., 2005), TransLM (using answers) (Xue et al., 2008) and CTM (Lee et al., 2008).”
Convolutional Neural Tensor Network Architecture for Community-Based Question Answering (2015, methodology): “• TransLM: We use translation-based language model of [Jeon et al., 2005] to calculate the similarity between two short-texts.”
FAQ-based Question Answering via Word Alignment (2015, methodology): “Another method treated this task as a statistical machine translation problem, and employed a parallel question set to learn word-to-word or phrase-to-phrase translation probabilities (Berger and Lafferty, 1999; Jeon et al., 2005; Lee et al., 2008; Xue et al., 2008; Bernhard and Gurevych, 2009; Zhou”
Learning to recognize reliable users and content in social media with coupled mutual reinforcement (2009, background): “[8] presented a machine translation model to find similar questions from a community QA service, but did not take quality of answers into consideration.”
Semi-supervised Question Retrieval with Gated Convolutions (2015, background): “Previous work on question retrieval has modeled this task using machine translation, topic modeling and knowledge graph-based approaches (Jeon et al., 2005; Li and Manandhar, 2011; Duan et al., 2008; Zhou et al., 2013).”