Information analysis and retrieval

Detecting early signatures of persuasion in information cascades

UMSI Assistant Professor Qiaozhu Mei is a contributing researcher on a project by Indiana University’s Center for Complex Networks and Systems Research to study early evidence of persuasion campaigns in online forums. The project, “Detecting Early Signatures of Persuasion in Information Cascades,” is funded by DARPA, the Defense Advanced Research Projects Agency of the federal government.

Wordsmith in the cloud: refining language models using web-scale language networks

In this project, UMSI Assistant Professor Qiaozhu Mei addressed the issue of text information overload generated from online conversations. Tools that effectively manage this information overload rely on statistical language models, yet the quality of these models is limited by the sparseness of data, the mismatch of context, and the incapability of modeling semantic relations.

Incentive centered design for information and communication systems

The Socio-Technical Infrastructure for Electronic Transactions (STIET) program, funded by a National Science Foundation IGERT Award, brings together faculty and doctoral students from the University of Michigan and Wayne State University in research, training, and outreach, through an incentive-centered design (ICD) approach to modern information systems.

Developing an intelligent, socially-oriented search recommendation service for electronic health records

This project researched the development of a search query recommendation service for health practitioners and researchers to help professionals retrieve information from electronic health records more easily and efficiently when using full-text search engines. This recommendation service would also allow users to develop and refine search queries for more effective searches in the future.

Integrative and in situ information retrieval and mining in online communities

This project, funded by a National Science Foundation CAREER Award, is the first integrative and in situ analysis of information generated in online communities that is of the people, by the people, and for the people. The user-centric Foreseer is the next generation of information analysis for online communities, with research that consists of formal community models, efficient data analysis tools, advanced solutions of real applications, and novel information systems.

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