{"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/learning-word-relatedness-over-time","title":"Learning Word Relatedness over Time","arxiv_id":"1707.08081","date":"2017-07-25","proceeding":"EMNLP 2017 9","authors":["Guy D. Rosin","Eytan Adar","Kira Radinsky"],"abstract":"Search systems are often focused on providing relevant results for the \"now\",\nassuming both corpora and user needs that focus on the present. However, many\ncorpora today reflect significant longitudinal collections ranging from 20\nyears of the Web to hundreds of years of digitized newspapers and books.\nUnderstanding the temporal intent of the user and retrieving the most relevant\nhistorical content has become a significant challenge. Common search features,\nsuch as query expansion, leverage the relationship between terms but cannot\nfunction well across all times when relationships vary temporally. In this\nwork, we introduce a temporal relationship model that is extracted from\nlongitudinal data collections. The model supports the task of identifying,\ngiven two words, when they relate to each other. We present an algorithmic\nframework for this task and show its application for the task of query\nexpansion, achieving high gain.","url_abs":"http://arxiv.org/abs/1707.08081v2","url_pdf":"http://arxiv.org/pdf/1707.08081v2.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":"learning-word-relatedness-over-time","repo_url":"https://github.com/guyrosin/learning-word-relatedness","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}