In this study we address the problem of answering queries over a peer-to-peer system of taxonomy-based sources. A taxonomy states subsumption relationships between negation-free DNF formulas on terms and negation-free conjunctions of terms. To the end of laying the foundations of our study, we first consider the centralized case, deriving the complexity of the decision problem and of query eval...

Mining generalized association rules among items in the presence of taxonomies has been recognized as an important model in data mining. Earlier work on mining generalized association rules ignore the fact that the taxonomies of items cannot be kept static while new transactions are continuously added into the original database. How to effectively update the discovered generalized association r...

Routing in ad-hoc networks, specifically intelligent-based ones, is a highly interested research topic in recent years. Most of them are simulation-based study. Large percentages have not even mentioned some of the fundamental parameters. This strictly reduces their validity and reliability. On the other hand, there is not a comprehensive framework to classify routing algorithms in wireless sen...

We present here an approach and algorithm for mining generalized term associations. The problem is to find co-occurrence frequencies of terms, given a collection of documents each with relevant terms, and a taxonomy of terms. We have developed an efficient Count Propagation Algorithm (CPA) targeted for library applications such as Medline. The basis of our approach is that sets of terms (termse...

The Benders decomposition algorithm has been successfully applied to a wide range of difficult optimization problems.This paper presents a state-of-the-art survey of this algorithm, with an emphasis on its use in combinatorial optimization. We discuss the classical algorithm, the impact of the problem formulation on its convergence, and the relationship to other decomposition methods. We introd...

Natural language generation systems rely on taxonomic thesauri for tasks such as lexical choice and aggregation. WordNet is one such taxonomy, but it is limited in size. Motivated by the needs of a generation system in the scientific literature domain, we present a method for building a taxonomic thesaurus from Wikipedia articles, where each article represents a potential concept in the taxonom...

Within the last 10 years, many model-based multi-objective optimization algorithms have been proposed. In this paper, a taxonomy of these algorithms is derived. It is shown which contributions were made to which phase of the MBMO process. A special attention is given to the proposal of a set of points for parallel evaluation within a batch. Proposals for four different MBMO algorithms are prese...

Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions is evolving into an important research area. Most conventional data-mining algorithms identify the relationships among transactions using binary values and find rules at a single concept level. Transactions with quantitative values and items with hierarchy rel...

The recent explosion of Web shops has made the user task of finding the desired products an increasingly difficult one. One way to solve this problem is to offer an integrated access to product information on the Web, for which an important component is the mapping of product taxonomies. In this paper, we introduce CMAP, an algorithm that can be used to map one product taxonomy to another produ...

The ability to automatically extract information from the footnotes of financial statements simplifies access to critical information concerning public companies. However, extraction can be particularly challenging due to great variations in the filing structure and terminologies used. Hierarchical formalization of text becomes a necessity in such circumstances. This is facilitated by the creat...