Query-sensitive embeddings
نویسندگان
چکیده
منابع مشابه
Hyperspherical Query Likelihood Models with Word Embeddings
This paper presents an initial study on hyperspherical query likelihood models (QLMs) for information retrieval (IR). Our motivation is to naturally utilize pretrained word embeddings for probabilistic IR. To this end, key idea is to directly leverage the word embeddings as random variables for directional probabilistic models based on von Mises-Fisher distributions that are familiar to cosine ...
متن کاملUsing Word Embeddings for Automatic Query Expansion
In this paper a framework for Automatic Query Expansion (AQE) is proposed using distributed neural language model word2vec. Using semantic and contextual relation in a distributed and unsupervised framework, word2vec learns a low dimensional embedding for each vocabulary entry. Using such a framework, we devise a query expansion technique, where related terms to a query are obtained by K-neares...
متن کاملQuery Clustering using Segment Specific Context Embeddings
This paper presents a novel query clustering approach to capture the broad interest areas of users querying search engines. We make use of recent advances in NLP word2vec and extend it to get query2vec, vector representations of queries, based on query contexts, obtained from the top search results for the query and use a highly scalable Divide & Merge clustering algorithm on top of the query v...
متن کاملQuery Expansion with Locally-Trained Word Embeddings
Continuous space word embeddings have received a great deal of attention in the natural language processing and machine learning communities for their ability to model term similarity and other relationships. We study the use of term relatedness in the context of query expansion for ad hoc information retrieval. We demonstrate that word embeddings such as word2vec and GloVe, when trained global...
متن کاملSearch Retargeting using Directed Query Embeddings
Determining user audience for online ad campaigns is a critical problem to companies competing in online advertising space. One of the most popular strategies is search retargeting, which involves targeting users that issued search queries related to advertiser’s core business, commonly specified by advertisers themselves. However, advertisers often fail to include many relevant queries, which ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: ACM Transactions on Database Systems
سال: 2007
ISSN: 0362-5915,1557-4644
DOI: 10.1145/1242524.1242525