Contact

Address:

No.1500, Shunhua Road, Jinan, Shandong Province, P.R. China, zipcode:250101

EMail:

nieliqiang at gmail dot com

Selected Projects

  • Healthcare System

    I lead a team to design and develop a community-based health system, named wenzher. To better serve health seekers, it automatically crawls and organizes multiple heterogeneous health-related sources. With state-of-the-art learning models, it intelligently mines the data insights and supports the following functions: deep text search, deep visual search, doctor recommendation, terminology annotation, symptom checker, disease report generation and other high-order analytics. It is publicly accessible via http://mmqa.nusidmi.com/mmqa/ or an open version http://healthqa.nusidmi.com:8082/.

  • University Ranking

    University ranking endeavors to play an unimaginable role in motivating and recognizing excellence, which greatly facilitates a wide range of stakeholders. Regarding such ranking, criticism often co-exists with praise. The controversial points of the current university ranking systems are threefold: 1) insufficient data, 2) labor-intensive user survey, and 3) naive fusion of multi-channel data. Towards these end, we present in this project a novel university ranking scheme to automatically and transparently rank universities by harvesting large-scale Web data from various views. The ranking results of Chinese universities are available here: http://unirank.nextcenter.org/home.

  • Micro-video Analysis

    The popularity of the traditional online video sharing platforms, like Youtube, has changed everything about the Internet. Servers like Youtube have enabled users to capture high-quality and long videos, upload and share them socially with everyone. But the late 2012 has seen a dramatic shift in the way Internet users digest videos: micro-videos spread rapidly across various online flagship platforms, such as Viddy, Vine, Instagram and Snapchat. Considering Vine as an example, as of December 2015, it has experienced an exponential explosion in its user and video base, reaching approximately 200 million active users monthly and 1.5 billion video loops daily. One reason that such bite-sized videos are gaining popularity is because users can conveniently shoot and instantly share videos via their smartphones without the need for professional camera work, editing, and, therefore, significant budgets. Besides, it takes seconds rather than minutes or even hours to view. The micro-video trends confirms this saying: "every good comes in small packages". We are currently working on the popularity prediction, venue category estimation, as well as advertisement of micro-videos.

  • Learning from Multiple Social Networks

    With the proliferation of social network services, more and more social users, such as individuals and organizations, are simultaneously involved in multiple social networks for various purposes. In fact, multiple social networks characterize the same social users from different perspectives, and their contexts are usually consistent or complementary rather than independent. Hence, as compared to using information from a single social network, appropriate aggregation of multiple social networks offers us a better way to comprehensively understand the given social users. My book on this project is available in Amazon. book

    We currently continue this research direction on learning from overlapping social networks and group profiling across multiple social networks.