Operators for Similarity Search: Semantics, Techniques and Usage Scenarios

Operators for Similarity Search
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Operators for Similarity Search. Semantics, Techniques and Usage Scenarios. Authors: P, Deepak, Deshpande, Prasad M. Free Preview. Introduces the field of . Operators for Similarity Search: Semantics, Techniques and Usage Scenarios This book provides a comprehensive tutorial on similarity operators.

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Walmart Services. Cambridge: Cambridge University Press, Modern information retrieval : the concepts and technology behind search.

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Harlow: Pearson, The approach combines theory, algorithms and practical examples. Osnova Introduction — What is searching, Things useful to know Support for Distributed Processing — Distributed file system, MapReduce, Algorithms using MapReduce, Cost model and performance evaluation Retrieval Operators and Result Evaluations — Common similarity search operators, Retrieval metrics Clustering — K-means algorithms, Clustering in non-Euclidean spaces, Clustering for streams and parallelism Finding Frequent Item Sets — Handling large datasets in main memory, Counting frequent items in a stream Finding Similar Items — Applications of near-neighbor search, Shingling of documents, Similarity-preserving summaries of sets, Locality sensitive hashing Searching in Data Streams — The stream data model, Filtering streams Link Analysis — Page Rank, Topic sensitive, Link spam Search Applications — Advertising on the web, Recommendation systems collaborative filtering , Mining social-network graphs Seznam.

Operators for similarity search : semantics, techniques and usage scenarios.

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Cham: Springer, Mining of massive datasets.