Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

article · Journal of Computational and Theoretical Nanoscience · 2018

Inducing and Refining Topics for Web Query Classification Using a Semantic Network

Rituparna Kumar, M. Chandrasekaran

Cited by 0Abstract and details only

Abstract

Web query classification, the task of inferring topical categories from a web search query is a non-trivial problem in Information Retrieval domain. The topic categories inferred by a Web query classification system may provide a rich set of features for improving query expansion and web advertising. Conventional methods for Web query classification derive corpus statistics from the web and employ machine-learning techniques to infer Open Directory Project categories. But they suffer from two major drawbacks, the computational overhead to derive corpus statistics and inferring topic categories that are too abstract for semantic discrimination due to polysemy. Concepts too shallow or too deep in the semantic gradient are produced due to the wrong senses of the query terms coalescing with the correct senses. This paper proposes and demonstrates a succinct solution to these problems through a method based on the Tree cut model and Wordnet Thesarus to infer fine-grained topic categories for Web query classification, and also suggests an enhancement to the Tree Cut Model to resolve sense ambiguities.

Cite this paper

APA 7

Kumar, R., & Chandrasekaran, M. (2018). Inducing and Refining Topics for Web Query Classification Using a Semantic Network. Journal of Computational and Theoretical Nanoscience, 15(2), 595–600. https://doi.org/10.1166/jctn.2018.7127

MLA 9

Kumar, Rituparna, and M. Chandrasekaran. “Inducing and Refining Topics for Web Query Classification Using a Semantic Network.” Journal of Computational and Theoretical Nanoscience, vol. 15, no. 2, 2018, pp. 595–600, https://doi.org/10.1166/jctn.2018.7127.

Chicago

Kumar, Rituparna, and M. Chandrasekaran. 2018. “Inducing and Refining Topics for Web Query Classification Using a Semantic Network.” Journal of Computational and Theoretical Nanoscience 15 (2): 595–600. https://doi.org/10.1166/jctn.2018.7127.

Harvard

Kumar, R. and Chandrasekaran, M. (2018) ‘Inducing and Refining Topics for Web Query Classification Using a Semantic Network’, Journal of Computational and Theoretical Nanoscience, 15(2), pp. 595–600. Available at: https://doi.org/10.1166/jctn.2018.7127.

BibTeX
@article{kumar2018inducing,
  title = {{Inducing and Refining Topics for Web Query Classification Using a Semantic Network}},
  author = {Kumar, Rituparna and Chandrasekaran, M.},
  journal = {Journal of Computational and Theoretical Nanoscience},
  volume = {15},
  number = {2},
  pages = {595--600},
  year = {2018},
  doi = {10.1166/jctn.2018.7127}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers