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Visual attention has long been an important topic in psychology and cognitive science. Recently, results from visual attention research (Haber et al. 2001; Myszkowski et al. 2001) are being adopted by computer graphics research. Due to speed limitations, there has been a movement to use a perception-based rendering approach where the rendering process(More)
We describe about the system description of the PSNUS team for the SemEval-2007 Web People Search Task. The system is based on the clustering of the web pages by using a variety of features extracted and generated from the data provided. This system achieves F α=0.5 = 0.75 and F α=0.2 = 0.78 for the final test data set of the task.
Traditionally, record linkage algorithms have played an important role in maintaining digital libraries - i.e., identifying matching citations or authors for consolidation in updating or integrating digital libraries. As such, a variety of record linkage algorithms have been developed and deployed successfully. Often, however, existing solutions have a set(More)
Ranking of publication venues is often closely related with important issues such as evaluating the contributions of individual scholars/research groups, or subscription decision making. The development of large-scale digital libraries and the availability of various meta data provide the possibility of building new measures more efficiently and accurately.(More)
The automation of extracting chemical names from text has significant value to biomedical and life science research. A major barrier in this task is the difficulty of getting a sizable and good quality data to train a reliable entity extraction model. Another difficulty is the selection of informative features of chemical names, since comprehensive domain(More)
Extractive multi-document summarization systems usually rank sentences in a document set with some ranking strategy and then select a few highly ranked sentences into the summary. One of the most popular ranking algorithms is the graph-based ranking algorithm. In this paper, we investigate making use of semantic role information to enhance the graph-based(More)
The problem of Twitter <i>user classification</i> using the <i>contents</i> of tweets is studied. We generate time series from tweets by exploiting the latent temporal information and solve the classification problem in time series domain. Our approach is inspired by the fact that Twitter users sometimes exhibit the <i>periodicity</i> pattern when they(More)
We present our vision and preliminary design toward web-crawled academic video search engine, named as LeeDeo, that can search, crawl, archive, index, and browse " academic " videos from the Web. Our proposal differs from existing general-purpose search engines such as Google or MSN whose focus is on the search of textual HTML documents or metadata of(More)
Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To address this challenge, we propose two novel semi-supervised clustering methods that incorporate prior knowledge in the form of pairwise cluster membership constraints. In particular , we(More)
—SAR codes are designed for transmission by a portable wireless device to provide high reliability and data rates on a wireless channel, while maintaining low human exposure to electromagnetic radiation. We provide design criteria and examples of SAR codes and show that a 3 dB reduction in exposure is within reach on some devices versus standard(More)