One of the obstacles to be overcome in Natural Language Understanding is the existence of lexical gaps; that is, words or word senses which are not in the lexicon of the system. No lexicon, whether hand-coded or derived ...

In neighborhood-based texture synthesis, adjacent local regions need to satisfy color continuity constraints in order to avoid visible seams. Such continuity constraints seriously restrict the variability of synthesized ...

This dissertation investigates novel approaches for analysis and visualization of two kinds of graph, scale-free network and rooted hierarchy, at large scales with thousands to millions of nodes. Scale-free network, ...

The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. Guarding data behind there, such query interfaces are the "entrances" or "doors" to the deep Web. ...

Large-scale networks, such as the Internet, cellular networks, play critical roles in today's life. The advancement of large-scale computer and communication networks heavily depends on the successful transformation from ...

Network algorithms are deployed on large networks, and proper algorithm evaluation is necessary to avoid large-scale outages or performance bottlenecks. However, evaluating a network algorithm in a simulator results ...

Wide-area Internet links are slow, expensive, and unreliable. This affects applications in two distinct ways. Back-end data processing applications, which need to transfer large amounts of data between data centers across ...

ESD design rule checking is different from the conventional design rule checking in that not only different rules have to be applied for different components in the ESD protection circuit, but also style of layout is of ...

Transactional memory (TM) is a compelling alternative to traditional synchronization, and implementing TM primitives directly in hardware offers a potential performance advantage over software-based methods. In this paper, ...

The proposed learning and inference frameworks have been applied to a variety of information extraction tasks, including entity extraction, entity/relation recognition, and semantic role labeling.