Αποδοτική διαχείριση κειμενικής πληροφορίας

Abstract

The basic goal of this thesis is to explore the possibilities of the field of computer science that deals with storing and processing information in the environment that formed by the modern applications. In recent years, the information that is available in electronic form, has met an enormous growth. Thus it is necessary to develop new techniques for efficient storage and processing. Two very specific and important applications in which constantly new problems arise are, the management of biological data, such as genome sequences, and the management information from the Web, such as documents HTML, XML or shortcuts (urls). The objective is the development of data structures for indexing information so that the questions are able to be answered in less time than looking explicitly in information. Such questions are to find patterns (pattern matching) or the identification of repeated motifs (motif extraction). In particular, the issues on which this thesis has focused are: - Locating Periodicities in strings. This section provides a series of algorithms for the extraction of periodicities of strings. We propose algorithms for the extraction of maximum repetitions of the cover, period and the seed of a string. The algorithms used are based on suffix tree and they are optimal. - Weighted Sequences indexing. In the next section, the study focuses on indexing of weighted sequences, and to answer questions like finding models, pairs, covers etc. in them. The weighted sequences are sequences where each position consists of all the symbols of the alphabet in sequence, having each one a specific weight. For the management of these sequences a particular indexing structure is proposed with the name Weighted Suffix Tree, a tree with structural features similar to those of the generalized suffix tree. In this work we propose the definition of the weighted suffix tree and construction algorithms in linear time and memory space. With the utilization of weighted suffix tree on a set of weighted sequences we propose algorithms for extracting repetitive structures from a set of weighted sequences. More specifically, we propose algorithms for finding maximum pairs, repeated motifs and common patterns of more than one weighted sequences -Recommendation Algorithms for web pages using strings processing algorithms. Several web applications (Recommendation systems or cache systems) want to predict the intentions of a visitor in order to propose or to preload a webpage. For this purpose systems try to exploit any experience that is recorded in the system from previous accesses. A new method for indexing and representing of information extracted is proposed upon the recorder data, from the user accesses in log files and content pages. For extracting knowledge from these data, the information is represented as strings and then treated and processed as weighted sequences. All these sequences are indexed by a generalized weighted sequence tree.