Computing and Informatics (E-Journal - Institute of Informatics, SAS, Bratislava)
Not a member yet
1506 research outputs found
Sort by
Self-Enriching Ontology-Based Casual Learning Games
Get PDFComputer games are currently one of the computer science applications with the highest amount of users. "Serious gaming" approaches try to use the attraction of playing games to convey serious content in an entertaining way. This paper presents a multi-agent-architecture for collaborative, serious and casual games. We are combining serious games with casual games, as these are known to have a high potential for frequent gaming by people of various social and educational background. To be flexible concerning the learning domain an ontology-based approach has been used. Thus, new games for different knowledge domains can be created by exchanging the ontology accordingly. Furthermore, we use a "game with a purpose" approach to enable the computer to learn new facts about the games knowledge domain to ease the effort of adapting the basic game to the intended target domain. The presented system is capable of proposing candidates for missing relations in the underlying ontology as well as pointing out possible misconceptions - either within the ontology or by the players - using various heuristics including "wisdom of the crowds" methodologies. The feasibility of the presented approach and its implementation (the Matchballs game) is shown by three case studies each focusing on one aspect of the system
How to Develop Pervasive Social Applications with the SAPERE Middleware
Get PDFSAPERE ("Self-Aware Pervasive Service Ecosystems'') is a general framework to support the decentralized execution of self-organizing pervasive computing services. In this paper we present the rationale underlying SAPERE and its reference conceptual architecture. Following, we sketch the middleware infrastructure of SAPERE and detail the interaction model implemented by it, based on a limited set of "eco-laws'' allowing general-purpose distributed self-organizing schemes. Finally, we show how a social application can be easily implemented exploiting such an infrastructure and report on performances
Distributed Agent-Based Online Auction System
Get PDFThis paper concerns the design and development of a distributed agent-based online system for English auctions. The proposed system is composed of two parts: an Agent-based Auction Server and a Web-based Graphical User Interface. The first part of our work brought about the advantages introduced by the multi-agent systems technology to the high-level of abstraction, modularity and performance of the server architecture and its implementation. On the server side, bids submitted by auction participants are handled by a hierarchical organization of agents that can be efficiently distributed on a computer network. This approach avoids the bottlenecks of bid processing that might occur during periods of heavy bidding, like for example snipping. We present experimental results that show a significant improvement of the server throughput compared with the architecture where a single auction manager agent is used for coordinating the participants for each active auction that is registered with the server. The second part of our work involved analysis of external functionalities, implementation and usability of a prototype online auction system that incorporates the Agent-based Auction Server. Our solution is outlined in terms of information flow management and its relation to the functionalities of the system. The main outcome of this part of the work is a clean specification of the information exchanges between the agent and non-agent software components of the system. Special attention is also given to the interoperability, understood here as successful integration of the different data communication protocols and software technologies that we employed for the implementation of the system
Discovering Relations by Entity Search in Lightweight Semantic Text Graphs
Get PDFEntity search is becoming a popular alternative for full text search. Recently Google released its entity search based on confirmed, human-generated data such as Wikipedia. In spite of these developments, the task of entity discovery, search, or relation search in unstructured text remains a major challenge in the fields of information retrieval and information extraction. This paper tries to address that challenge, focusing specifically on entity relation discovery. This is achieved by processing unstructured text using simple information extraction methods, building lightweight semantic graphs and reusing them for entity relation discovery by applying algorithms from graph theory. An important part is also user interaction with semantic graphs, which can significantly improve information extraction results and entity relation search. Entity relations can be discovered by various text mining methods, but the advantage of the presented method lies in the similarity between the lightweight semantics extracted from a text and the information networks available as structured data. Both graph structures have similar properties and similar relation discovery algorithms can be applied. In addition, we can benefit from the integration of such graph data. We provide both a relevance and performance evaluations of the approach and showcase it in several use case applications
A Large Spanish-Catalan Parallel Corpus Release for Machine Translation
Get PDFWe present a large Spanish-Catalan parallel corpus extracted from ten years of the paper edition of a bilingual Catalan newspaper. The produced corpus of 7.5 M parallel sentences (around 180 M words per language) is useful for many natural language applications. We report excellent results when building a statistical machine translation system trained on this parallel corpus. The Spanish-Catalan corpus is partially available via ELDA (Evaluations and Language Resources Distribution Agency) in catalog number ELRA-W0053
XML and Fuzzy-Based Two Various Knowledge Retrieval Methods in Edaphology
Get PDFIn this paper, we propose a proficient method for knowledge retrieval in edaphology to assist the edaphologists and those who are related with agriculture in a big way. The proposed method mainly consists of two phases of which the first one is to build the knowledge base using XML and the latter part deals with information retrieval using fuzzy search. Initially, the relational database is converted to XML database. This paper discusses two algorithms, one is when the soil characteristics are given as input to have the plant list and in the other, plant names are given as input to have the soil characteristics suited for the plant. While retrieving the query result, the crisp numerical values are converted to fuzzy value using the triangular fuzzy membership function and matched to those in database. Those which satisfy are added to the result list and subsequently, the frequency is found out to rank the result list so as to obtain the final sorted list. Performances metrics are used in order to evaluate the method and compared to baseline paper to identify the number of plants retrieved, ranking efficiency, and computation time and memory usage. Results obtained proved the validity of the method and the method obtained the average computation time of 0.102 seconds and average memory usage of 2 486 Kb, which are all far better than our previous method results
The Cost of Trust in the Dynamics of Best Attachment
Get PDFThe need of trust is growing in several contexts as e-commerce, virtual communities, distributed on-line services and many others as an essential precautionary component for users during interactions with strangers, either other people or virtual agents. Generally trust metrics endorse the principle "the higher the trust, the more legitimate that user will be''; a consequence is that getting trusted must require some effort, otherwise all participants would easily achieve high trustworthiness. In this work we study how a user can achieve and preserve a good trust and what costs it requires over time; we also investigate some heuristics that allow reducing the complexity in exploring the rank-effort space especially for large networks
A Natural Hand Gesture System for People with Brachial Plexus Injuries
Get PDFThis paper focuses on a design case study of a natural hand gesture system for users with intact motion control of the metacarpophalangeal joint and thumb basal joint of the hand after brachial plexus injuries. The lexicon of hand gestures had eight entries and was demonstrated to be natural and ergonomic with the limited hand motions. A cooperative multi-cue system was proposed for the key hand posture recognition of the proposed hand gestures. We utilized the designed system into a remote smart car control and electric wheelchair control. Experimental a results demonstrated the robustness and potential feasibility of the system in human-computer interaction for the proposed users
MetroNG: Computer-Aided Scheduling and Collision Detection
Get PDFIn this paper, we propose a formal model of the objects involved in a class of scheduling problems, namely in the classroom scheduling in universities which allow a certain degree of liberty in their curricula. Using the formal model, we present efficient algorithms for the detection of collisions of the involved objects and for the inference of a tree-like navigational structure in an interactive scheduling software allowing a selection of the most descriptive view of the scheduling objects. These algorithms were used in a real-world application called MetroNG; a visual interactive tool that is based on more than 10 years of experience we have in the field. It is currently used by the largest universities and colleges in the Czech Republic. The efficiency and usability of MetroNG suggests that our approach may be applied in many areas where multi-dimensionally structured data are presented in an interactive application
Improving Efficiency of Incremental Mining by Trie Structure and Pre-Large Itemsets
Get PDFIncremental data mining has been discussed widely in recent years, as it has many practical applications, and various incremental mining algorithms have been proposed. Hong et al. proposed an efficient incremental mining algorithm for handling newly inserted transactions by using the concept of pre-large itemsets. The algorithm aimed to reduce the need to rescan the original database and also cut maintenance costs. Recently, Lin et al. proposed the Pre-FUFP algorithm to handle new transactions more efficiently, and make it easier to update the FP-tree. However, frequent itemsets must be mined from the FP-growth algorithm. In this paper, we propose a Pre-FUT algorithm (Fast-Update algorithm using the Trie data structure and the concept of pre-large itemsets), which not only builds and updates the trie structure when new transactions are inserted, but also mines all the frequent itemsets easily from the tree. Experimental results show the good performance of the proposed algorithm