D-Index & Metrics Best Publications

Lili Cheng

Microsoft (United States)
United States

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 49 Citations 9,112 98 World Ranking 3867 National Ranking 1970

Overview

What is she best known for?

The fields of study she is best known for:

Operating system
The Internet
World Wide Web

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.

Her most cited work include:

Computer system architecture for automatic context associations (700 citations)
Social mapping of contacts from computer communication information (420 citations)
Systems and methods for sharing dynamic content among a plurality of online co-users (310 citations)

What are the main themes of her work throughout her whole career to date?

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.

She most often published in these fields:

World Wide Web (37.17%)
Information retrieval (16.81%)
Human–computer interaction (14.16%)

What were the highlights of her more recent work (between 2010-2017)?

World Wide Web (37.17%)
Human–computer interaction (14.16%)
Set (5.31%)

In recent papers she was focusing on the following fields of study:

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.

Between 2010 and 2017, her most popular works were:

Event planning within social networks (75 citations)
Electronic message organization via social groups (67 citations)
Shared electronic incentives and coupons leveraging social connections and shepherding (60 citations)

In her most recent research, the most cited papers focused on:

Operating system
The Internet
Computer network

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.