12562104
Collaborative information agents on the World Wide Web
In this paper, we present DIAMS, a system of distributed, collaborative information agents which help users access, collect, organize and exchange information on the World Wide Web. Personal agents provide their owners dynamic displays of well organized information collections, as well as friendly information management utilities. Personal agents exchange information with one another. They also work with other types of information agents such as matchmakers and knowledge experts to facilitate collaboration and communication.
28375225
User-centered indexing for adaptive information access
We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Learning and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.
7673579
Managing personal and group collections of information
The internet revolution has dramatically increased the amount of information available to users. Various tools such as search engines have been developed to help users find the information they need from this vast repository. Users often also need tools to help manipulate the growing amount of useful information they have discovered. Current tools available for this purpose are typically local components of web browsers designed to manage URL bookmarks. They provide limited functionalities to handle high information complexities.
12280706
A distributed multi-agent system for collaborative information management and sharing
In this paper, we present DIAMS, a system of distributed, collaborative agents to help users access, manage, share and exchange information. A DIAMS personal agent helps its owner find information most relevant to current needs. It provides tools and utilities for users to manage their information repositories with dynamic organization and virtual views. Flexible hierarchical display is integrated with indexed query search to support effective information access. Automatic indexing methods are employed to support user queries and communication between agents.
2426986
Quantifying Privacy Leakage through Answering Database Queries
We assume a database consists of records of individuals with private or sensitive fields. Queries on the distribution of a sensitive field within a selected population in the database can be submitted to the data center. The answers to the queries leak private information of individuals though no identification information is provided. Inspired by decision theory, we present a quantitative model for the privacy protection problem in such a database query or linkage environment in this paper. In the model, the value of information is estimated from the viewpoint of the querier.To estimate the value, we define the information state of the data user by a class of probability distributions on the set of possible confidential values. We further define the usefulness of information based on how easy the data user can locate individuals that fit the description given in the queries. These states and the usefulness of information can be modified and refined by the user's knowledge acquisition actions. The value of information is then defined as the expected gain of the privacy receiver and the privacy is protected by imposing costs on the answers of the queries for balancing the gain.
11313417
Correlated MIMO Rayleigh fading systems with transmit channel state information
We analyze the capacity of correlated multiple-input-multiple-output (MIMO) channels when channel state information (CSI) is available at both the transmitter and the receiver. We show that the achievable rate by using simple beamforming can approach this capacity when the MIMO channels are highly correlated. To simplify the coding/decoding and power adaption, we apply truncated channel inversion (TCI) in MIMO correlated channels and evaluate the achievable rates. The results show that in highly correlated MIMO fading channels, beamforming combined with TCI can get close to capacity. This provides a simplified near optimum coding, as beamforming with TCI requires only one code designed for the AWGN channel and one coder/decoder pair.
33856120
Probability model for faults in large-scale multicomputer systems
Reliability and availability are critical when faults appear in the design of large multicomputer systems. On the other hand, it is very difficult to predict the reliability and availability of multicomputer systems. In this paper, we study the reliability and availability of large multicomputer systems under a more realistic model in which each network node has an independent failure probability. We mainly consider the reliability and availability of large mesh-connected multicomputer systems. The metric is connectivity probability of networks. In a previous work (J. Chen and T. Wang, Proc. 14th Int. Conf. Parallel and Distr. Comp. and Sys., pp. 606-611, 2002), we proved that if the node failure probability is fixed, then the connectivity probability of mesh networks can be arbitrarily small when the network size is sufficiently large. Thus, it is practically important for multicomputer system manufacturers to determine the upper bound for node failure probability, when the probability of network connectivity and the network size are given. We develop another novel technique to formally derive lower bounds on the connectivity probability for mesh networks. Our study shows that mesh networks of practical size can tolerate a large number of faulty nodes and thus are reliable enough for multicomputer systems. For example, we formally prove that as long as the node failure probability is bounded by 0.09% (note that according to current VLSI technology, building network nodes with failure probability under 0.09% is achievable), mesh networks of up to a million nodes remain connected with a probability larger than 99%. The results for mesh network reliability and availability are obtained by formal and thorough mathematical proofs.
1746401
On the Effective Enumerability of NP Problems
In the field of computational optimization, it is often the case that we are given an instance of an NP problem and asked to enumerate the first few best solutions to the instance. Motivated by this, we propose in this paper a new framework to measure the effective enumerability of NP optimization problems. More specifically, given an instance of an NP problem, we consider the parameterized problem of enumerating a given number of best solutions to the instance, and study its average complexity in terms of the number of solutions. Our framework is different from the previously-proposed ones. For example, although it is known that counting the number of k-paths in a graph is #W[1]-complete, we present a fixed-parameter enumeration algorithm for the problem. We show that most algorithmic techniques for fixed-parameter tractable problems, such as search trees, color coding, and bounded treewidth, can be used for parameterized enumerations. In addition, we design elegant and new enumeration techniques and show how to generate small-size structures and enumerate solutions efficiently.
9144862
Rules and fuzzy rules in text: concept, extraction and usage
Several concepts and techniques have been imported from other disciplines such as Machine Learning and Artificial Intelligence to the field of textual data. In this paper, we focus on the concept of rule and the management of uncertainty in text applications. The different structures considered for the construction of the rules, the extraction of the knowledge base and the applications and usage of these rules are detailed. We include a review of the most relevant works of the different types of rules based on their representation and their application to most of the common tasks of Information Retrieval such as categorization, indexing and classification.