Her primary areas of investigation include World Wide Web, Cloud computing, Computer security, Human–computer interaction and Component. Her study focuses on the intersection of World Wide Web and fields such as Data science with connections in the field of Event. Her research integrates issues of Keying, Networking hardware, Thin client and Cryptography in her study of Cloud computing.
Her biological study spans a wide range of topics, including Identity, Search engine indexing and Information repository. Her study in Human–computer interaction is interdisciplinary in nature, drawing from both Standardization, Visualization and Interface. Her work carried out in the field of Component brings together such families of science as Space, Multimedia, Object, Information retrieval and Network mapping.
Lili Cheng mainly focuses on World Wide Web, Information retrieval, Human–computer interaction, Database and Subject matter. As a member of one scientific family, Lili Cheng mostly works in the field of World Wide Web, focusing on Order and, on occasion, Content management. Her Information retrieval study combines topics from a wide range of disciplines, such as Metadata, Set and Taxonomy.
Her Human–computer interaction research includes themes of User interface, Interface, Service and Visualization. Lili Cheng has included themes like Spatial query and Computer network in her Database study. Her Cloud computing study incorporates themes from restrict and Software.
Lili Cheng spends much of her time researching World Wide Web, Human–computer interaction, Set, Information retrieval and Subject matter. Her work on Social network, Personalization and User profile as part of general World Wide Web research is frequently linked to Plan and Mechanism, bridging the gap between disciplines. Her study in the field of Mode also crosses realms of Computing systems.
Her Set research is multidisciplinary, incorporating perspectives in Data type and Service. Her research links Subject with Information retrieval. While the research belongs to areas of Web query classification, Lili Cheng spends her time largely on the problem of Query language, intersecting her research to questions surrounding Component.
Lili Cheng focuses on World Wide Web, Social network, Incentive, Information retrieval and Set. She studies User profile, a branch of World Wide Web. Her research in Social network intersects with topics in Event, Event planning and Web search query.
Incentive is connected with Address book, Coupon, Order, Marketing and Database transaction in her research. Her work blends Information retrieval and Subject matter studies together.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Computer system architecture for automatic context associations
Shelly D. Farnham;Andrzej Turski;David P. Vronay;Lili Cheng.
Social mapping of contacts from computer communication information
Shelly D. Farnham;Andrzej Turski;William L. Portnoy;David P. Vronay.
Systems and methods for sharing dynamic content among a plurality of online co-users
Oliver Lee;Quji Guo;Joel K. Grossman;Brian D. Wentz.
Sharing media objects in a network
Sean Kelly;Lili Cheng;Shelly Farnham;William Portnoy.
Data security in an off-premise environment
Henricus Johannes Maria Meijer;William H. Gates;Raymond E Ozzie;Thomas F. Bergstraesser.
Personal data mining
Raymond E. Ozzie;William H. Gates;Gary W. Flake;Thomas F. Bergstraesser.
Rights management in a cloud
William H. Gates;Ira L. Snyder;Thomas F. Bergstraesser;Arnold N. Blinn.
Remote management of resource license
Henricus Johannes Maria Meijer;William H. Gates;Thomas F. Bergstraesser;Lili Cheng.
Resource standardization in an off-premise environment
Henricus Johannes Maria Meijer;Thomas F. Bergstraesser;Christopher W. Brumme;Lili Cheng.
Aggregated resource license
Nishant V. Dani;William H. Gates;Thomas F. Bergstraesser;Lili Cheng.
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.
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