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  <titleInfo>
    <title>Mining of massive datasets</title>
  </titleInfo>
  <name type="personal">
    <namePart>Jurij Leskovec ; Anand Rajaraman ; Jeffrey D Ullman</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Anand Rajaraman; Jeffrey D Ullman</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="">Data mining-Big data</genre>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">xxu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Cambridge</placeTerm>
    </place>
    <publisher>: Cambridge University Press</publisher>
    <dateIssued>, 2014</dateIssued>
    <edition>2nd edition</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>xii, 467 pages ;24 cm.</extent>
  </physicalDescription>
  <abstract>	
This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction. It includes a range of over 150 challenging exercises.</abstract>
  <tableOfContents>	Data mining --
MapReduce and the new software stack --
Finding similar items --
Mining data streams --
Link analysis --
Frequent itemsets --
Clustering --
Advertising on the Web --
Recommendation systems --
Mining social-network graphs --
Dimensionality reduction --
Large-scale machine learning.</tableOfContents>
  <note type="statement of responsibility">/Jurij Leskovec</note>
  <subject>
    <topic>Computer Science</topic>
  </subject>
  <classification authority="ddc">006.312 LES</classification>
  <identifier type="issn">9781316638491</identifier>
  <identifier type="">Atlantic Publishers &amp; Distributors (P)LTD. ;7/22,Anasri Road, Daryaganj,New Delhi-110002</identifier>
  <recordInfo>
    <recordCreationDate encoding="marc">180917</recordCreationDate>
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