Hung-Hsuan Chen

Pennsylvania State University | Penn State

CiteSeerX is a digital library search engine that provides access to more than 4 million academic documents with nearly a million users and millions of hits per day. Artificial intelligence (AI) technologies are used in many components of CiteSeerX e.g. to accurately extract metadata, intelligently crawl the web, and ingest documents. We present ke...

Discovering the relationships of gene to gene, gene to its related diseases, and diseases implicated in common genes is important. However, traditional biological methods can be expensive. Here, we show that the diseases implicated in common genes and the genes related to a multiple-gene disease can be inferred by the vertex similarity measures, a...

Discovering similar objects in a social network has many interesting issues. Here, we present ASCOS, an Asymmetric Structure COntext Similarity measure that captures the similarity scores among any pairs of nodes in a network. The definition of ASCOS is similar to that of the well-known SimRank since both define score values recursively. However, w...

We propose CSSeer, a free and publicly available keyphrase based recommendation system for expert discovery based on the CiteSeerX digital library and Wikipedia as an auxiliary resource. CSSeer generates keyphrases from the title and the abstract of each document in CiteSeerX. These keyphrases are then utilized to infer the authors' expertise. We c...

Recent studies show that vertex similarity measures are good at predicting link formation over the near term, but are less effective in predicting over the long term. This indicates that, generally, as links age, their degree of influence diminishes. However, few papers have systematically studied this phenomenon. In this paper, we apply a supervis...

With the popularity of online social network services, influence maximization on social networks has drawn much attention in recent years. Most of these studies approximate a greedy based sub-optimal solution by proving the submodular nature of the utility function. Instead of using the analytical techniques, we are interested in solving the diffus...

We provide an overview of some of the specialized datasets that were created for various projects related to the CiteSeer x digital library. These datasets are not those usually available from CiteSeer x and awareness of these datasets may further advance state-of-the-art research in academic digital library data management and analysis.

Vertex similarity measure is a useful tool to discover the hidden relationships of vertices in a complex network. We introduce relation strength similarity (RSS), a vertex similarity measure that could better capture potential relationships of real world network structure. RSS is unique in that is is an asymmetric measure which could be used for a...

We introduce the graph vertex similarity measure, Relation Strength Similarity (RSS), that utilizes a network's topology to discover and capture similar vertices. The RSS has the advantage that it is asymmetric; can be used in a weighted network; and has an adjustable "discovery range" parameter that enables exploration of friend of friend connecti...

Collaborative research has been increasingly popular and important in academic circles. However, there is no open platform available for scholars or scientists to effectively discover potential collaborators. This paper discusses CollabSeer, an open system to recommend potential research collaborators for scholars and scientists. CollabSeer discove...

In search engines, ranking algorithms measure the importance and relevance of documents mainly based on the contents and relationships between documents. User attributes are usually not considered in ranking. This user-neutral approach, however, may not meet the diverse interests of users, who may demand different documents even with the same queri...

To improve the search results for socially-connect users, we propose a ranking framework, Social Network Document Rank (SNDocRank). This framework considers both document contents and the similarity between a searcher and document owners in a social network and uses a Multi-level Actor Similarity (MAS) algorithm to efficiently calculate user simila...

Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users' interests and preferences are often diverse, and may demand different results even with the same queries. How can we integrate user interests in ranking algorithms to improve s...

This paper presents MobiSNA - a mobile video social networking application that supports the exploration, sharing, and creation of video contents through social networks. The MobiSNA project provides the user with an easy to use experience of accessing video content from mobile devices (e.g., mobile phones, PDAs) over wireless broadband networks (e...

This paper proposes an application-level multicast framework based on peer-to-peer communications to improve performance of large scale VOD services. Since the deployment of multicast-enabled network is still not popular nowadays, developing an application-level multicast infrastructure to support multicast delivery would be a good alternative. We...

This paper presents MobiSNA - a mobile video social networking application that supports the exploration, sharing, and creation of video contents through social networks. The MobiSNA project provides the user with an easy to use experience of accessing video content from mobile devices (e.g., mobile phones, PDAs) over wireless broadband networks (e...