Ivan Obradović

Automatic construction of a morphological dictionary of multi-word units

The development of a comprehensive morphological dictionary of multi-word units for Serbian is a very demanding task, due to the complexity of Serbian morphology. Manual production of such a dictionary proved to be extremely time-consuming. In this paper we present a procedure that automatically produces dictionary lemmas for a given list of multi-word units. To accomplish this task the procedure relies on data in e-dictionaries of Serbian simple words, which are already well developed. We also offer an evaluation of the proposed procedure on several different sets of data. Finally, we discuss some implementation issues and present how the same procedure is used for other languages.

An intelligent hybrid system for surface coal mine safety analysis

Analysis of safety in surface coal mines represents a very complex process. Published studies on mine safety analysis are usually based on research related to accidents statistics and hazard identification with risk assessment within the mining industry. Discussion in this paper is focused on the application of AI methods in the analysis of safety in mining environment. Complexity of the subject matter requires a high level of expert knowledge and great experience. The solution was found in the creation of a hybrid system PROTECTOR, whose knowledge base represents a formalization of the expert knowledge in the mine safety field. The main goal of the system is the estimation of mining environment as one of the significant components of general safety state in a mine. This global goal is subdivided into a hierarchical structure of subgoals where each subgoal can be viewed as the estimation of a set of parameters (gas, dust, climate, noise, vibration, illumination, geotechnical hazard) which determine the general mine safety state and category of hazard in mining environment. Both the hybrid nature of the system and the possibilities it offers are illustrated through a case study using field data related to an existing Serbian surface coal mine.

Corpora Issues in Validation of Serbian Wordnet

In this paper we describe how the existing monolingual Serbian corpus, the bilingual Serbian/English (S/E) and Serbian/French (S/F) aligned corpora, and the appropriate morphological e-dictionaries, have been used in validation, development, and refinement of Serbian WordNet. The influence of different derivational processes, e.g. derivation of augmentatives/diminutives and possessive adjectives from nouns, to the structure of Serbian synsets is examined. A part of the experimental results that justify the applied approach is given.

SFILTEX: toward an expert system for time-series filter design

This paper describes an attempt to develop a statistical expert system (FILTEX) as an intelligent aid for time-series filter design. To this end the knowledge of the filter design strategy is represented in Prolog and coupled with numerical routines of a general purpose signal processing package. This knowledge-based system is conceived as a set of independent knowledge sources integrated into a system by a blackboard mechanism which embodies overall control of the filter design process. Modularity and flexibility of knowledge representation in such a framework preserve usability of the evolving system during its development from the original numerical package to an expert system for filter design. This approach seems to be more flexible than the use of shells and less time consuming than building from scratch. A novel method for incorporating classical statistical information into an uncertainty management mechanism is presented. Experimental results confirm the feasibility of the approach and set direct...

Improving Document Retrieval in Large Domain Specific Textual Databases Using Lexical Resources

Large collections of textual documents represent an example of big data that requires the solution of three basic problems: the representation of documents, the representation of information needs and the matching of the two representations. This paper outlines the introduction of document indexing as a possible solution to document representation. Documents within a large textual database developed for geological projects in the Republic of Serbia for many years were indexed using methods developed within digital humanities: bag-of-words and named entity recognition. Documents in this geological database are described by a summary report, and other data, such as title, domain, keywords, abstract, and geographical location. These metadata were used for generating a bag of words for each document with the aid of morphological dictionaries and transducers. Named entities within metadata were also recognized with the help of a rule-based system. Both the bag of words and the metadata were then used for pre-indexing each document. A combination of several \(tf\_idf\) based measures was applied for selecting and ranking of retrieval results of indexed documents for a specific query and the results were compared with the initial retrieval system that was already in place. In general, a significant improvement has been achieved according to the standard information retrieval performance measures, where the InQuery method performed the best.

Prediction of flyrock launch velocity using artificial neural networks

Due to a potential to cause damage to machinery and structures and cause injuries to personnel, flyrock is the most dangerous adverse effect of blasting operations. Because of that, it is of primary importance to predict flyrock events and maximum range of flyrock fragments in order to define safety limits and secure the perimeter. There are various models for flyrock range prediction, and most of them rely on proper calculations of flyrock launch velocity. However, a unique and universally applicable model of launch velocity prediction still does not exist. Work presented in this article is a concept of adaptive system application for the prediction of flyrock launch velocities. It shows the principles of input data selection, acquisition and processing and presents the principles of design, training, validation and verification of applied artificial neural network.

Indexing of Textual Databases Based on Lexical Resources: A Case Study for Serbian

In this paper we describe an approach to improvement of information retrieval results for large textual databases by pre-indexing documents using bag-of-words and named entity recognition. The approach was applied on a database of geological projects financed by the Republic of Serbia for several decades now. Each document within this database is described by a summary report, consisting of metadata on the geological project, such as title, domain, keywords, abstract, and geographical location. A bag of words was produced from these metadata with the help of morphological dictionaries and transducers, while named entities were recognized using a rule-based system. Both were then used for pre-indexing documents for information retrieval purposes where ranking of retrieved documents was based on several

Frame-based blackboard expert system for signal processing

tf\_idf