Results 11 to 20 of about 49,185 (256)
Causal Pathway Extraction from Web-Board Documents
Applied Sciences, 2021 This research aim is to extract causal pathways, particularly disease causal pathways, through cause-effect relation (CErel) extraction from web-board documents.
Chaveevan Pechsiri, Rapepun Piriyakul
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ViCo: Word Embeddings From Visual Co-Occurrences [PDF]
2019 IEEE/CVF International Conference on Computer Vision (ICCV), 2019 Accepted to ICCV 2019. Project Page: http://tanmaygupta.info/vico/
Tanmay Gupta +2 more
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Automatic Keywords Extraction Based on Co-Occurrence and Semantic Relationships Between Words
IEEE Access, 2020 Automatic keywords extraction is a method that extracts words or phrases from a document which can express the main idea of the document. In this paper, we propose an unsupervised keywords extraction framework for individual documents, which improves the
Xiangke Mao +3 more
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Co-occurrence of reduced word forms in natural speech [PDF]
Interspeech 2012, 2012 Interspeech 2012, 09 september ...
Viebahn, M., Ernestus, M., McQueen, J.
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Co-citation and co-occurrence analysis of scientific productions in water pollution field [PDF]
مجله علمسنجی کاسپین, 2023 Background and aim: Co-citation and word co-occurrence analysis can help to identify key articles in any subject area. Therefore, the purpose of the current paper is to identify the thematic orientation in the co-citation and co-occurrence network of ...
Nosrat Riahinia +2 more
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Dimension-reduced estimation of word co-occurrence probability [PDF]
Proceedings of the 38th Annual Meeting on Association for Computational Linguistics - ACL '00, 2000 We investigate a novel approach to solve the problem of sparse data through dimension reduction. Linear algebraic technique called LSA/SVD is used to find co-relationships of sparse words. Three variant estimation methods are suggested and they are evaluated for estimating unseen noun-verb co-occurrence probability.
Kilyoun Kim, Key-Sun Choi
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A Pitman-Yor Process Self-Aggregated Topic Model for Short Texts of Social Media
IEEE Access, 2021 In recent years, with the rapid growth of social media, short texts have been very prevalent on the internet. Due to the limited length of each short text, word co-occurrence information in this type of documents is sparse.
Yue Niu, Hongjie Zhang, Jing Li
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Retrieving collocations by co-occurrences and word order constraints [PDF]
Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics -, 1997 In this paper, we describe a method for automatically retrieving collocations from large text corpora. This method retrieve collocations in the following stages: 1) extracting strings of characters as units of collocations 2) extracting recurrent combinations of strings in accordance with their word order in a corpus as collocations. Through the method,
Sayori Shimohata +2 more
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Exploring the Relationship between Social Media and Tourist Experiences: A Bibliometric Overview
Social Sciences, 2023 In recent years, the relationship between the tourism experience and social media has become an increasingly popular research topic. Previous research has focused only on certain aspects of the tourism experience and social media, but none have covered ...
Samia Idbenssi +3 more
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ESTeR: Combining Word Co-occurrences and Word Associations for Unsupervised Emotion Detection [PDF]
Findings of the Association for Computational Linguistics: EMNLP 2020, 2020 Accurate detection of emotions in user- generated text was shown to have several applications for e-commerce, public well-being, and disaster management. Currently, the state-of-the-art performance for emotion detection in text is obtained using complex, deep learning models trained on domain-specific, labeled data. In this paper, we propose ESTeR , an
Sujatha Das Gollapalli +2 more
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