{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/predicting-user-intent-from-search-queries","title":"Predicting user intent from search queries using both CNNs and RNNs","arxiv_id":"1812.07324","date":"2018-12-18","proceeding":null,"authors":["Mihai Cristian Pîrvu","Alexandra Anghel","Ciprian Borodescu","Alexandru Constantin"],"abstract":"Predicting user behaviour on a website is a difficult task, which requires\nthe integration of multiple sources of information, such as geo-location, user\nprofile or web surfing history. In this paper we tackle the problem of\npredicting the user intent, based on the queries that were used to access a\ncertain webpage. We make no additional assumptions, such as domain detection,\ndevice used or location, and only use the word information embedded in the\ngiven query. In order to build competitive classifiers, we label a small\nfraction of the EDI query intent prediction dataset\n\\cite{edi-challenge-dataset}, which is used as ground truth. Then, using\nvarious rule-based approaches, we automatically label the rest of the dataset,\ntrain the classifiers and evaluate the quality of the automatic labeling on the\nground truth dataset. We used both recurrent and convolutional networks as the\nmodels, while representing the words in the query with multiple embedding\nmethods.","url_abs":"http://arxiv.org/abs/1812.07324v1","url_pdf":"http://arxiv.org/pdf/1812.07324v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"predicting-user-intent-from-search-queries","repo_url":"https://github.com/Morphl-AI/MorphL-Model-User-Search-Intent","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}