2017 - ACM Distinguished Member
2007 - ACM Senior Member
Sihem Amer-Yahia mainly investigates XML, Information retrieval, World Wide Web, XML database and Efficient XML Interchange. His study in XML is interdisciplinary in nature, drawing from both Ranking, Matching, Tree and Pattern matching. His study focuses on the intersection of Tree and fields such as Key with connections in the field of Algorithm and Theoretical computer science.
His research on Information retrieval focuses in particular on Query language. His work on Recommender system as part of general World Wide Web research is frequently linked to Attendance, thereby connecting diverse disciplines of science. His XML database research includes themes of XML Signature, Document Structure Description, XML schema, XML validation and Streaming XML.
Information retrieval, World Wide Web, Data science, XML and Crowdsourcing are his primary areas of study. His Information retrieval research is multidisciplinary, incorporating perspectives in XML validation, Efficient XML Interchange and XML database. His work on Recommender system, Social web and Social network as part of general World Wide Web study is frequently linked to Diversity, bridging the gap between disciplines.
His Data science study combines topics in areas such as Variety, Social media, Sentence and Data management. His work carried out in the field of XML brings together such families of science as Query language, Database, Structure and Ranking. His study in Crowdsourcing is interdisciplinary in nature, drawing from both Approximation algorithm and Set.
His primary scientific interests are in Data science, Artificial intelligence, Machine learning, Domain and Analytics. His Data science research includes themes of Data management, Variety, Semantics, Behavioral analytics and Visualization. Sihem Amer-Yahia interconnects Graph and Multi-core processor in the investigation of issues within Artificial intelligence.
His study in the fields of Deep learning, Artificial neural network, Missing data and Decision tree under the domain of Machine learning overlaps with other disciplines such as Architecture. His Analytics research incorporates elements of Entropy, Stratified sampling, Social web and Cohort. His Social web study results in a more complete grasp of World Wide Web.
Sihem Amer-Yahia focuses on Analytics, Social web, Data science, Approximation algorithm and Key. His Analytics study which covers Data analysis that intersects with Data visualization and Visualization. The concepts of his Data science study are interwoven with issues in Sentence, Optimization problem and Crowdsourcing.
His Approximation algorithm research incorporates themes from Multi-objective optimization, Theoretical computer science and Group. His studies in Key integrate themes in fields like Information retrieval, Data structure and Cohort. His Demographics research overlaps with Domain, World Wide Web, Usability, Publishing and Publication.
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Group recommendation: semantics and efficiency
Sihem Amer-Yahia;Senjuti Basu Roy;Ashish Chawlat;Gautam Das.
very large data bases (2009)
Automatic construction of travel itineraries using social breadcrumbs
Munmun De Choudhury;Moran Feldman;Sihem Amer-Yahia;Nadav Golbandi.
acm conference on hypertext (2010)
Minimization of tree pattern queries
Sihem Amer-Yahia;SungRan Cho;Laks V. S. Lakshmanan;Divesh Srivastava.
international conference on management of data (2001)
FleXPath: flexible structure and full-text querying for XML
Sihem Amer-Yahia;Laks V. S. Lakshmanan;Shashank Pandit.
international conference on management of data (2004)
Tree Pattern Relaxation
Sihem Amer-Yahia;SungRan Cho;Divesh Srivastava.
extending database technology (2002)
It takes variety to make a world: diversification in recommender systems
Cong Yu;Laks Lakshmanan;Sihem Amer-Yahia.
extending database technology (2009)
Structure and content scoring for XML
Sihem Amer-Yahia;Nick Koudas;Amélie Marian;Divesh Srivastava.
very large data bases (2005)
Texquery: a full-text search extension to xquery
S. Amer-Yahia;C. Botev;J. Shanmugasundaram.
the web conference (2004)
Tree pattern query minimization
S. Amer-Yahia;S. Cho;L. V. S. Lakshmanan;D. Srivastava.
very large data bases (2002)
Task assignment optimization in knowledge-intensive crowdsourcing
Senjuti Basu Roy;Ioanna Lykourentzou;Saravanan Thirumuruganathan;Sihem Amer-Yahia.
very large data bases (2015)
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