206625201
Web Intelligence (WI)
This paper is about a new research field called Web Intelligence (WI for short). We try to explain the needs for coining the term as a sub-discipline of computer science for systematic studies on advanced Web related theories and technologies, as well as the design and implementation of Intelligent Web Information Systems (IWIS). Background information and related topics are discussed in an attempt to demonstrate why we consider WI to be a subject worthy of study and, at the same time, to establish a starting point for the further development of WI.
9590852
Web-based information retrieval support systems: building research tools for scientists in the new information age
The concept of Web-based information retrieval support systems (WIRSS) is introduced. The needs for WIRSS are shown by a detailed case study of existing research article indexing and citation analysis systems, such as current content, DBLP, science citation index and CiteSeer. The objective of WIRSS is to build new and effective research tools for scientists to access, explore and use information on the Web, which may lead to improved research productivity and quality.
6507492
Induction of Classification Rules by Granular Computing
A granular computing model is used for learning classification rules by considering the two basic issues: concept formation and concept relationships identification. A classification rule induction method is proposed. Instead of focusing on the selection of a suitable partition, i.e., a family of granules defined by values of an attribute, in each step, we concentrate on the selection of a single granule. This leads to finding a covering of the universe, which is more general than partition based methods. For the design of granule selection heuristics, several measures on granules are suggested.
2932585
A Granular Computing Approach to Machine Learning
The key to granular computing is to make use of granules in problem solving. Classification is one of the well studied problems in machine learning and data mining as it involves of discovery knowledge from large databases. We presents a granular computing view to classification problems and propose a granular computing approach to classification in this paper. The ID3 [8] and PRISM [2] algorithma are studied and extended to granular computing algorithm.
449421
Web-based Research Support Systems
Web-based research support systems (WRSS) are a specific type of Web-based support systems (WSS) that support research activities for scientists. They are motivated by the challenges and opportunities of the Web, as well as the needs of scientists. The recent advancements of computer and Web technologies make the implementation of WSS feasible. A general framework of WSS is presented by considering its basic issues. Within the framework, the principles and issues of WRSS are examined. From the conceptual point of view, WRSS may be considered as a new subfield of study. It focuses on a more systematic and coherent treatment of existing isolated studies of research support. From the implementation point of view, WRSS are based on assembling, integration, and adaptation of existing computer technology and information systems for the purpose of research support. The results of WRSS may lead to new and viable research tools.
1875630
A Comparative Study of Fuzzy Sets and Rough Sets
This paper reviews and compares theories of fuzzy sets and rough sets. Two approaches for the formulation of fuzzy sets are reviewed, one is based on many-valued logic and the other is based on modal logic. Two views of rough sets are presented, set-oriented view and operator-oriented view. Rough sets under set-oriented view are closely related to fuzzy sets, which leads to non-truth-functional fuzzy set operators. Both of them may be considered as deviations of classical set algebra. In contrast, rough sets under operator-oriented view are different from fuzzy sets, and may be regarded as an extension of classical set algebra.
3194628
Generalization of Hadamard Matrices and a Class of Two-Dimensional Error-Correcting Codes
12920787
Deterministic multiuser carrier-frequency offset estimation for interleaved OFDMA uplink
In orthogonal frequency-division multiple access (OFDMA), closely spaced multiple subcarriers are assigned to different users for parallel signal transmission. An interleaved subcarrier-assignment scheme is preferred because it provides maximum frequency diversity and increases the capacity in frequency-selective fading channels. The subcarriers are overlapping, but orthogonal to each other such that there is no intercarrier interference (ICI). Carrier-frequency offsets (CFOs) between the transmitter and the receiver destroy the orthogonality and introduces ICI, resulting in multiple-access interference. This paper exploits the inner structure of the signals for CFO estimation in the uplink of interleaved OFDMA systems. A new uplink signal model is presented, and an estimation algorithm based on the signal structure is proposed for estimating the CFOs of all users using only one OFDMA block. Diversity schemes are also presented to improve the estimation performance. Simulation results illustrate the high accuracy and efficiency of the proposed algorithm.
6831644
Outage performance of a hybrid DS/FH spread-spectrum signal in an ISM band
This paper develops an analytical model for characterizing the coexistence interference in the unlicensed industrial, scientific and medical (ISM) bands, based on radio frequency measurement results in the 2.4 GHz ISM band. The modeling approach presented here offers a simple methodology for profiling the interference from devices occupying a common spectrum. Outage performance using the interference model is exemplified through the analysis for a hybrid direct-sequence frequency-hopping spread-spectrum signal. The work presented in this paper looks to provide insight by means of quantitative evaluation of signal outage in a coexistence environment that can be used for engineering design of applications for unlicensed bands as well as function as a tool in the development process for future spectrum management policy models.
17927523
An energy-efficient and access latency optimized indexing scheme for wireless data broadcast
Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by means of hash-based indexing and enables nonflat data broadcast to reduce access latency. The design of hash function and the optimization of bandwidth allocation are investigated in depth to refine MHash. Experimental results show that, under skewed access distribution, MHash outperforms state-of-the-art air indexing schemes and achieves access latency close to optimal broadcast scheduling