A Digital Library of Folklore Songs and Keyword-Based Search Engine

ACM Computing Classification System (1998): H3.3, H.5.5, J5.

Automated System for Effective Internet Marketing Campaign (ASEIMC)

The purpose of the paper is to present an automated system for realization of effective internet marketing campaign (ASEIMC). The constantly growing number of websites available online brings more problems for the contemporary enterprises to reach their potential customers. Therefore the companies have to discover novel approaches to increase their online sales. The presented ASEIMC system gives such an approach and helps small and medium enterprises to compete for customers with big corporations in the Internet space.

Analysis and Coordination of Expert Statements in the Problems of Intellectual Information Search

* This work was financially supported by RFBF-04-01-00858.

Effectiveness of Title-Search vs. Full-Text Search in the Web

Search engines sometimes apply the search on the full text of documents or web-pages; but sometimes they can apply the search on selected parts of the documents only, e.g. their titles. Full-text search may consume a lot of computing resources and time. It may be possible to save resources by applying the search on the titles of documents only, assuming that a title of a document provides a concise representation of its content. We tested this assumption using Google search engine. We ran search queries that have been defined by users, distinguishing between two types of queries/users: queries of users who are familiar with the area of the search, and queries of users who are not familiar with the area of the search. We found that searches which use titles provide similar and sometimes even (slightly) better results compared to searches which use the full-text. These results hold for both types of queries/users. Moreover, we found an advantage in title-search when searching in unfamiliar areas because the general terms used in queries in unfamiliar areas match better with general terms which tend to be used in document titles.

A Variable Neighborhood Search Approach for Solving the Maximum Set Splitting Problem

This paper presents a Variable neighbourhood search (VNS) approach for solving the Maximum Set Splitting Problem (MSSP). The algorithm forms a system of neighborhoods based on changing the component for an increasing number of elements. An efficient local search procedure swaps the components of pairs of elements and yields a relatively short running time. Numerical experiments are performed on the instances known in the literature: minimum hitting set and Steiner triple systems. Computational results show that the proposed VNS achieves all optimal or best known solutions in short times. The experiments indicate that the VNS compares favorably with other methods previously used for solving the MSSP. ACM Computing Classification System (1998): I.2.8.

Teaching Materials Repository

The paper presents results from the development of a methodology and corresponding software tools for building an academic repository. The repository was filled up with gaming material. The repository architecture and key features of the search engine are discussed. The emphasis falls on solutions of the large set of problems concerning the development of proper mechanisms for semantics-based search in a digital repository.

Bulgarian Folk Songs in a Digital Library

The paper presents the main results of an ongoing project aimed at the development of technologies for digitization of Bulgarian folk music and building a heterogeneous digital library with Bulgarian folk songs presented with their music, notes and text. An initial digitization and preservation of the Bulgarian cultural heritage starts by means of digitization and insertion into the library of over 1000 songs that were recorded and written down during the 60s and 70s of XX century. Also we present a full text search engine in a collection of lyrics (text of songs) and coded notes (symbolic melody). Some perspectives for future projects are also discussed.

Automatic Classification of Bulgarian Adjectives on Emotional Semantic Axes

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

One Class of Stochastic Local Search Algorithms

Accelerated probabilistic modeling algorithms, presenting stochastic local search (SLS) technique, are considered. General algorithm scheme and specific combinatorial optimization method, using “golden section” rule (GS-method), are given. Convergence rates using Markov chains are received. An overview of current combinatorial optimization techniques is presented.

Evolutionary Technique of Shorter Route Determination of Fire Brigade Following to Fire Place with the Optimized Space of Search

In this paper the technique of shorter route determination of fire engine to the fire place on time minimization criterion with the use of evolutionary modeling is offered. The algorithm of its realization on the base of complete and optimized space of search of possible decisions is explored. The aspects of goal function forming and program realization of method having a special purpose are considered. Experimental verification is executed and the results of comparative analysis with the expert conclusions are considered.

Finding the Relationship between a Search Algorithm and a Class of Functions on Discrete Space by Exhaustive Search

* The work is supported by RFBR, grant 04-01-00858-a.

Optimization of ATM Telecommunication Networks

ATM network optimization problems defined as combinatorial optimization problems are considered. Several approximate algorithms for solving such problems are developed. Results of their comparison by experiments on a set of problems with random input data are presented.

Optimization of Gabor Wavelets for Face Recognition

The article describes researches of a method of person recognition by face image based on Gabor wavelets. Scales of Gabor functions are determined at which the maximal percent of recognition for search of a person in a database and minimal percent of mistakes due to false alarm errors when solving an access control task is achieved. The carried out researches have shown a possibility of improvement of recognition system work parameters in the specified two modes when the volume of used data is reduced.

Solving the Task Assignment Problem with a Variable Neighborhood Search

In this paper a variable neighborhood search (VNS) approach for the task assignment problem (TAP) is considered. An appropriate neighborhood scheme along with a shaking operator and local search procedure are constructed specifically for this problem. The computational results are presented for the instances from the literature, and compared to optimal solutions obtained by the CPLEX solver and heuristic solutions generated by the genetic algorithm. It can be seen that the proposed VNS approach reaches all optimal solutions in a quite short amount of computational time.

Variable Neighborhood Search for the File Transfer Scheduling Problem

ACM Computing Classification System (1998): I.2.8, G.1.6.