Sense-Based Topic Word Embedding Model for Item Recommendation
نویسندگان
چکیده
منابع مشابه
A Topic Model for Word Sense Disambiguation
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic posterior inference algorithm for simultaneously disambiguating a corpus and learning the domains in which to consider each word. Using the WORDNET hierarchy, we embed the construction of Abney and Light (1999) in the to...
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Conventional word sense induction (WSI) methods usually represent each instance with discrete linguistic features or cooccurrence features, and train a model for each polysemous word individually. In this work, we propose to learn sense embeddings for the WSI task. In the training stage, our method induces several sense centroids (embedding) for each polysemous word. In the testing stage, our m...
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To learn users’ preference, their feedback information is commonly modeled as scalars and integrated into matrix factorization (MF) based algorithms. Based on MF techniques, the preference degree is computed by the product of user and item vectors, which is also represented by scalars. On the contrary, in this paper, we express users’ feedback as constrained vectors, and call the idea constrain...
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This paper describes our system for shared task 13 “Word Sense Induction for Graded and Non-Graded Senses” of SemEval-2013. The task is on word sense induction (WSI), and builds on earlier SemEval WSI tasks in exploring the possibility of multiple senses being compatible to varying degrees with a single contextual instance: participants are asked to grade senses rather than selecting a single s...
متن کاملSimple Embedding-Based Word Sense Disambiguation
We present a simple knowledge-based WSD method that uses word and sense embeddings to compute the similarity between the gloss of a sense and the context of the word. Our method is inspired by the Lesk algorithm as it exploits both the context of the words and the definitions of the senses. It only requires large unlabeled corpora and a sense inventory such as WordNet, and therefore does not re...
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2909578