7663373
Performance analysis of multipath multistage interconnection networks with nonuniform output traffic distribution
Develops the analysis of output buffers in multipath multistage interconnection networks. The delay-throughput performance of output buffers in multipath interconnection networks is closely related to the output traffic distribution, which is the distribution of packet arrival rates at each output link connected to a given output module. Many multipath networks produce nonuniform output traffic distributions, even if the input traffic pattern is uniform. We propose in this paper a performance model for output buffer analysis with respect to such a nonuniform output traffic distribution and analyze the output buffer performance of several multipath networks by our proposed analysis model. It is shown that the output traffic distributions are different for the various multipath networks and the output buffer performance (such as packet loss probability and delay) gets better as the nonuniformity of the output traffic distribution becomes higher.
32944410
SPHINX - A Hybrid Knowledge Representation System
39501622
A logic programming approach to hybrid knowledge representation
A new hybrid system called Sphinx is presented which combines classification-based reasoning with logic programming technique. It consists of two major components: a terminological component and an assertional one. The former uses a frame-based knowledge representation scheme based on classification and the latter is a theorem prover based on Horn logic. The assertional component can also handle a first-order query language and wh-questions. A new knowledge base maintenance mechanism based on the negation as failure inference rule enables Sphinx to support incremental assertions and retractions. In addition, Sphinx provides explanation capability to help the user in developing and debugging knowledge bases.
3145493
KPSP: A Knowledge Programming System based on Prolog
29923826
A Relational Dataflow Database Machine Based on Hierarchical Ring Network
1326236
History Sensitive String for Multiple Alphabets
In most cases, to represent characters in a computer, conventional code systems such as ASCII, EBCDIC, or BCD, whose code-length is uniform, have been used. In some countries, where the native language is not English, people can easily adapt their alphabet to these code systems by simply replacing the Enghsh alphabet with the alphabet of their native language. In other countries, especially in Korea and Japan, a straightforward application of the conventional code system is not possible. This is because, to compose a sentence, people customarily intermix words each of which may be constructed by different alphabets. For example, in Korea, they have an alphabet for their native language called Hangul. Hangul is a complete language by which Koreans can communicate with each other. However, Korean culture was influenced by China and more recently by the western countries. This results in widespread usage of four different types of documents in Korea. Documents may be written in Hangul only, Hangul with Chinese words, Hangul with English words, and Hangul with both Chinese and English words. Even in these cases, Hangul is the main alphabet. Another example of the applications of multiple alphabets in a single text are the high level language programs in Korean environment where the program language is a popular high level language such as PASCAL, C, or LISP, but variable names or data in the program may consist of Korean characters [7,9]. In this case, the main alphabet is English. Another example using heterogeneous characters is the use of attributes such as color, size, or font in high quality text editors. In such cases, characters from multiple alphabets should be used in a computer. Since each alphabet may have characteristics different from each other, some coding methods for multiple alphabets can be considered. When the sizes of the alphabets are significantly different from each other, employment of codes of a uniform length is prohibitively expensive. There are two different techniques to encode the multiple alphabets into a single code system. In the following sections, two coding methods of multiple alphabets are generalized, and their advantages and disadvantages are analyzed.
30331490
Robust Watermarking on Polygonal Meshes Using Distribution of Vertex Norms
Most watermarking techniques for 3-D mesh models have mainly focused on robustness against various attacks, such as adding noise, smoothing, simplification, re-meshing, clipping, and so on. These attacks perceptually damage the stego model itself. Unlike watermarking of other multimedia data, serious attacks for 3-D meshes includes similarity transform and vertex re-ordering. They can fatally destroy the watermark without any perceptual degradation of the stego model. In this paper, we propose a new watermarking technique for 3-D polygonal mesh model, which modifies the distribution of vertex norms according to watermark bit to be embedded. In particular, the proposed employs blind watermark detection technique, which extracts the watermark without referring to cover meshes. The simulation results show that the proposed is remarkably robust against similarity transform and vertex re-ordering.
7057212
Modeling and managing content changes in text databases
Large amounts of (often valuable) information are stored in Web-accessible text databases. "Metasearchers" provide unified interfaces to query multiple such databases at once. For efficiency, metasearchers rely on succinct statistical summaries of the database contents to select the best databases for each query. So far, database selection research has largely assumed that databases are static, so the associated statistical summaries do not need to change over time. However, databases are rarely static and the statistical summaries that describe their contents need to be updated periodically to reflect content changes. In this paper, we first report the results of a study showing how the content summaries of 152 real Web databases evolved over a period of 52 weeks. Then, we show how to use "survival analysis" techniques in general, and Cox's proportional hazards regression in particular, to model database changes over time and predict when we should update each content summary. Finally, we exploit our change model to devise update schedules that keep the summaries up to date by contacting databases only when needed, and then we evaluate the quality of our schedules experimentally over real Web databases.
2425278
Shuffling a Stacked Deck: The Case for Partially Randomized Ranking of Search Engine Results
In-degree, PageRank, number of visits and other measures of Web page popularity significantly influence the ranking of search results by modern search engines. The assumption is that popularity is closely correlated with quality, a more elusive concept that is difficult to measure directly. Unfortunately, the correlation between popularity and quality is very weak for newly-created pages that have yet to receive many visits and/or in-links. Worse, since discovery of new content is largely done by querying search engines, and because users usually focus their attention on the top few results, newly-created but high-quality pages are effectively "shut out," and it can take a very long time before they become popular.We propose a simple and elegant solution to this problem: the introduction of a controlled amount of randomness into search result ranking methods. Doing so offers new pages a chance to prove their worth, although clearly using too much randomness will degrade result quality and annul any benefits achieved. Hence there is a tradeoff between exploration to estimate the quality of new pages and exploitation of pages already known to be of high quality. We study this tradeoff both analytically and via simulation, in the context of an economic objective function based on aggregate result quality amortized over time. We show that a modest amount of randomness leads to improved search results.
2800780
Page quality: in search of an unbiased web ranking
In a number of recent studies [4, 8] researchers have found that because search engines repeatedly return currently popular pages at the top of search results, popular pages tend to get even more popular, while unpopular pages get ignored by an average user. This "rich-get-richer" phenomenon is particularly problematic for new and high-quality pages because they may never get a chance to get users' attention, decreasing the overall quality of search results in the long run. In this paper, we propose a new ranking function, called page quality that can alleviate the problem of popularity-based ranking. We first present a formal framework to study the search engine bias by discussing what is an "ideal" way to measure the intrinsic quality of a page. We then compare how PageRank, the current ranking metric used by major search engines, differs from this ideal quality metric. This framework will help us investigate the search engine bias in more concrete terms and provide clear understanding why PageRank is effective in many cases and exactly when it is problematic. We then propose a practical way to estimate the intrinsic page quality to avoid the inherent bias of PageRank. We derive our proposed quality estimator through a careful analysis of a reasonable web user model, and we present experimental results that show the potential of our proposed estimator. We believe that our quality estimator has the potential to alleviate the rich-get-richer phenomenon and help new and high-quality pages get the attention that they deserve.
10280309
Analysis of User Web Traffic with A Focus on Search Activities
Although search engines are playing an increasingly important role in users’ Web access, our understanding is still limited regarding the magnitude of search-engine influence. For example, how many times do people start browsing the Web from a search engine? How much percentage of Web traffic is incurred as a result of search? To what extent does a search engine like Google extend the scope of Websites that users can reach? To study these issues, in this paper we analyze a real Web access trace collected over a period of two and half months from the UCLA Computer Science Department. Our study indicates that search engines influence about 13.6% of the users’ Web traffic directly and indirectly. In addition, our study provides realistic estimates for certain key parameters used for Web modelling.