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Word embedding techniques (e.g., Word2Vec, GloVe) have been recently used for variety of applications with quite good rate of success. They allow to capture word semantics and syntactics with decreased dimensionality based on the concept of distributional vector representations. Vector representations can be then used for similarity comparison. However, if we treat the word embeddings as a kind of...
We propose a method to generate effective query suggestions aiming to help struggling search, where users experience difficulty in locating information that is relevant to their information need in the search session. The core is identifying struggling component of an on-going struggling session and mining the effective representations of it. The struggling component is the semantic component of information...
Numerous archives and collections of past documents have become available recently thanks to mass scale digitization and preservation efforts. Libraries, national archives, and other memory institutions have started opening up their collections to interested users. Yet, searching within such collections usually requires knowledge of appropriate keywords due to different context and language of the...
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