{"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-neural-word-salience-scores","title":"Learning Neural Word Salience Scores","arxiv_id":"1709.01186","date":"2017-09-04","proceeding":"SEMEVAL 2018 6","authors":["Krasen Samardzhiev","Andrew Gargett","Danushka Bollegala"],"abstract":"Measuring the salience of a word is an essential step in numerous NLP tasks.\nHeuristic approaches such as tfidf have been used so far to estimate the\nsalience of words. We propose \\emph{Neural Word Salience} (NWS) scores, unlike\nheuristics, are learnt from a corpus. Specifically, we learn word salience\nscores such that, using pre-trained word embeddings as the input, can\naccurately predict the words that appear in a sentence, given the words that\nappear in the sentences preceding or succeeding that sentence. Experimental\nresults on sentence similarity prediction show that the learnt word salience\nscores perform comparably or better than some of the state-of-the-art\napproaches for representing sentences on benchmark datasets for sentence\nsimilarity, while using only a fraction of the training and prediction times\nrequired by prior methods. Moreover, our NWS scores positively correlate with\npsycholinguistic measures such as concreteness, and imageability implying a\nclose connection to the salience as perceived by humans.","url_abs":"http://arxiv.org/abs/1709.01186v1","url_pdf":"http://arxiv.org/pdf/1709.01186v1.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-neural-word-salience-scores","repo_url":"https://github.com/bollegala/repseval","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-similarity","task_name":"Sentence Similarity"},{"task_slug":"word-embeddings","task_name":"Word Embeddings"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1709.01186","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}