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020 _a9783319787534
_9978-3-319-78753-4
024 7 _a10.1007/978-3-319-78753-4
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _a5th International Symposium on Data Mining Applications
_h[electronic resource] /
_cedited by Mamdouh Alenezi, Basit Qureshi.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVI, 248 p. 98 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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_2rda
490 1 _aAdvances in Intelligent Systems and Computing,
_x2194-5365 ;
_v753
505 0 _a1. Use of Machine Learning for Rate Adaptation in MPEG-DASH for Quality of Experience Improvement -- 2. An Analysis of Traffic Accident in KSA,Riyadh by Using Clustering Techniques -- 3. The Effect of Vitamin B12 Deficiency on Blood Count Using Data Mining -- 4.Support of Existing Chatbot Development Framework for Arabic Language: A Brief Survey -- 5. Pattern Orientation in Arabic Corpus Annotation and a Proposed Pattern Ontology -- 6. A Benchmark Collection for Program Objectives Mapping to ABET Outcomes: Accreditation -- 7. Bug Reports Evolution in Open Source System -- 8. Analysis of Call Detail Records for Understanding Users Behavior and Anomaly Detection Using Neo4j -- 9.Empirical Analysis of Static Code Metrics for Predicting Risk Scores in Android Applications -- 10.Toward Stream Analysis of Software Debugging Data.
520 _aThe 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and machine learning researchers in Saudi Arabia, Gulf Cooperation Council (GCC) countries and the Middle East region. This book gathers the proceedings of the SDMA 2018. All papers were peer-reviewed based on a strict policy concerning the originality, significance to the area, scientific vigor and quality of the contribution, and address the following research areas. • Applications: Applications of data mining in domains including databases, social networks, web, bioinformatics, finance, healthcare, and security. • Algorithms: Data mining and machine learning foundations, algorithms, models, and theory. • Text Mining: Semantic analysis and mining text in Arabic, semi-structured, streaming, multimedia data. • Framework: Data mining frameworks, platforms and systems implementation. • Visualizations: Data visualization and modeling.
650 0 _aComputational intelligence.
_97716
650 0 _aArtificial intelligence.
_93407
650 1 4 _aComputational Intelligence.
_97716
650 2 4 _aArtificial Intelligence.
_93407
700 1 _aAlenezi, Mamdouh.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_951048
700 1 _aQureshi, Basit.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_951049
710 2 _aSpringerLink (Online service)
_951050
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319787527
776 0 8 _iPrinted edition:
_z9783319787541
830 0 _aAdvances in Intelligent Systems and Computing,
_x2194-5365 ;
_v753
_951051
856 4 0 _uhttps://doi.org/10.1007/978-3-319-78753-4
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c78699
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