S
Shaul Markovitch
Researcher at Technion – Israel Institute of Technology
Publications - 110
Citations - 7668
Shaul Markovitch is an academic researcher from Technion – Israel Institute of Technology. The author has contributed to research in topics: Heuristics & Tree (data structure). The author has an hindex of 32, co-authored 108 publications receiving 7381 citations. Previous affiliations of Shaul Markovitch include University of Michigan & Google.
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Proceedings Article
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
TL;DR: This work proposes Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from Wikipedia that results in substantial improvements in correlation of computed relatedness scores with human judgments.
Proceedings ArticleDOI
A word at a time: computing word relatedness using temporal semantic analysis
TL;DR: This paper proposes a new semantic relatedness model, Temporal Semantic Analysis (TSA), which captures this temporal information in word semantics as a vector of concepts over a corpus of temporally-ordered documents.
Proceedings Article
Overcoming the brittleness bottleneck using wikipedia: enhancing text categorization with encyclopedic knowledge
TL;DR: It is proposed to enrich document representation through automatic use of a vast compendium of human knowledge--an encyclopedia, and empirical results confirm that this knowledge-intensive representation brings text categorization to a qualitatively new level of performance across a diverse collection of datasets.
Journal ArticleDOI
Wikipedia-based semantic interpretation for natural language processing
TL;DR: This work proposes a novel method, called Explicit Semantic Analysis (ESA), for fine-grained semantic interpretation of unrestricted natural language texts, which represents meaning in a high-dimensional space of concepts derived from Wikipedia, the largest encyclopedia in existence.
Journal ArticleDOI
Concept-Based Information Retrieval Using Explicit Semantic Analysis
TL;DR: This article introduces a new concept-based retrieval approach based on Explicit Semantic Analysis (ESA), a recently proposed method that augments keyword-based text representation with concept- based features, automatically extracted from massive human knowledge repositories such as Wikipedia.