Query expansion using lexical-semantic relations

By Ellen M. Voorhees. 1994

Subfields: Information Retrieval & Search, Natural Language Processing

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Citations in the corpus

Pretrained Transformers for Text Ranking: BERT and Beyond (2020, background): “[2019b] answered this question by comparing a number of prominent interaction-based and representation-based neural ranking models to a well-engineered implementation of bag-ofwords querying with well-tuned query expansion on the dataset from the TREC 2004 Robust Track [Voorhees, 2004]. Under this l”
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval (2020, methodology): “Query Expansion Techniques in IR As our dense encoder augments the original question with the initial retrieved results to form the updated query representation, our work is also relevant to query expansion techniques (Rocchio, 1971; Voorhees, 1994; Ruthven & Lalmas, 2003) that are widely used in tr”
Document Expansion by Query Prediction (2019, background): “Approaches to tackling the vocabulary mismatch problem within these constraints include relevance feedback (Rocchio, 1971), query expansion (Voorhees, 1994; Xu and Croft, 2000), and modeling term relationships using statistical translation (Berger and Lafferty, 1999).”
Entity based Q&A Retrieval (2012, methodology): “Some expand queries using word relationships derived from co-occurrence thesaurus (Bai et al., 2005; Qiu and Frei, 1993), hand-crafted thesaurus (Liu et al., 2004; Voorhees, 1994) and combination of both (Cao et al., 2005).”
Personalized query expansion for the web (2007, background): “were controversial, either reporting improvements, or even reductions in output quality [36].”
Query expansion using local and global document analysis (1996, background): “There is, however, little evidence that a general thesaurus is of any use in improving the effectiveness of the search, even if words are selected by the searchers [Voorhees, 1994].”
A semiotic metrics suite for assessing the quality of ontologies (2005, background): “SRS follows the tradition of query expansion in Information Retrieval (IR) [16, 31].”
Integrating and Evaluating Neural Word Embeddings in Information Retrieval (2015, methodology): “Automatic query expansion based on crafted linguistic resources such as WordNet have not led to substantial improvements in effectiveness [29].”
Estimating Embedding Vectors for Queries (2016, methodology): “There are a number of query expansion methods based on linguistic resources such as WordNet, but they have not substantially improved the retrieval performance [34].”
ReQ-ReC: high recall retrieval with query pooling and interactive classification (2014, methodology): “Other query reformulation methods can also be applied, such as synonym expansion [24] and semantic term matching [5].”
Estimation of statistical translation models based on mutual information for ad hoc information retrieval (2010, background): “Many studies have tried to bridge the vocabulary gap between documents and queries both based on co-occurrence thesaurus [1, 9, 14, 21, 24, 31, 32, 38] and hand-crafted thesaurus [15, 35].”
Query Expansion by Mining User Logs (2003, background): “One can refer to [33] for some examples of utilization of such a resource for query expansion.”
Embedding-based Query Language Models (2016, methodology): “There are a number of query expansion methods based on linguistic resources, such as WordNet, but they have not substantially improved the retrieval performance [26].”
Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning (2020, background): “To help capture the semantics of the query rather than its bag of words, queries are typically expanded [23, 71] to include synonyms and semantically close words.”