The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Short Text Similarity with Word Embeddings
Open accessAbstract
Determining semantic similarity between texts is important in many tasks in information retrieval such as search, query suggestion, automatic summarization and image finding. Many approaches have been suggested, based on lexical matching, handcrafted patterns, syntactic parse trees, external sources of structured semantic knowledge and distributional semantics. However, lexical features, like string matching, do not capture semantic similarity beyond a trivial level. Furthermore, handcrafted patterns and external sources of structured semantic knowledge cannot be assumed to be available in all circumstances and for all domains. Lastly, approaches depending on parse trees are restricted to syntactically well-formed texts, typically of one sentence in length.
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Cites
Glove: Global Vectors for Word Representation
Pennington, J., Socher, R., & Manning, C. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1162 · Cited by 34,071
Efficient Estimation of Word Representations in Vector Space
Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1301.3781 · Cited by 26,568
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533
Convolutional Neural Networks for Sentence Classification
Kim, Y. (2014) · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.3115/v1/d14-1181 · Cited by 14,831
Indexing by latent semantic analysis
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 · Cited by 12,751
A unified architecture for natural language processing: deep neural networks with multitask learning
Collobert, R., & Weston, J. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390177 · Cited by 5,058
Distributed Representations of Sentences and Documents
Le, Q. V., & Mikolov, T. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1405.4053 · Cited by 4,934
Natural language processing with Python
Bird, S., Klein, E., & Loper, E. (2009) · CERN Document Server (European Organization for Nuclear Research) · Cited by 3,468
The probabilistic relevance framework: BM25 and beyond
Robertson, S., & Zaragoza, H. (2009) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000019 · Cited by 3,374
Reasoning With Neural Tensor Networks for Knowledge Base Completion
Socher, R., Chen, D., Manning, C. D., & Ng, A. Y. (2013) · Cited by 1,667
Cited by
BioWordVec, improving biomedical word embeddings with subword information and MeSH
Zhang, Y., Chen, Q., Yang, Z., Lin, H., & Lu, Z. (2019) · Scientific Data · doi:10.1038/s41597-019-0055-0 · Cited by 455
Semantic similarity metrics for evaluating source code summarization
Haque, S., Eberhart, Z., Bansal, A., & McMillan, C. (2022) · Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension · doi:10.1145/3524610.3527909 · Cited by 116
Measuring text similarity based on structure and word embedding
Farouk, M. (2020) · Cognitive Systems Research · doi:10.1016/j.cogsys.2020.04.002 · Cited by 47
The Effect of Audiences on the User Experience with Conversational Interfaces in Physical Spaces
Candello, H., Pinhanez, C., Pichiliani, M., Cavalin, P., Figueiredo, F., Vasconcelos, M., & Do Carmo, H. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300320 · Cited by 33
Recent Advances in Generative Information Retrieval
Tang, Y., Zhang, R., Guo, J., & de Rijke, M. (2023) · Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region · doi:10.1145/3624918.3629547 · Cited by 22
Self-citation
Metadata
- Authors
- Kenter, T., & de Rijke, M.
- Venue
- Proceedings of the 24th ACM International on Conference on Information and Knowledge Management
- Publisher
- ACM
- Published
- 2015-10-17
- Pages
- 1411-1420
- OpenAlex
- W2028742638
- Cited by
- 440
- References
- 33
- FWCI
- 23.86
- Type
- conference paper
- Language
- en
- Open access
- green
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