A. Tsanousa, L. Angelis, Stavroula Ntoufa, N. Papakonstantinou, K. Stamatopoulos
{"title":"A Structural Equation Modeling Approach of the Toll-Like Receptor Signaling Pathway in Chronic Lymphocytic Leukemia","authors":"A. Tsanousa, L. Angelis, Stavroula Ntoufa, N. Papakonstantinou, K. Stamatopoulos","doi":"10.1109/DEXA.2013.37","DOIUrl":"https://doi.org/10.1109/DEXA.2013.37","url":null,"abstract":"Gene pathway identification is an open and active research area that has attracted the interest not only of biomedical scientists but also of a large number of researchers from disciplines related to knowledge discovery from biological data. In this paper, we used Structural Equation Modeling (SEM) in order to statistically investigate the Toll-Like Receptor (TLR) signaling pathway in Chronic Lymphocytic Leukemia (CLL). Specifically, we used Path Analysis, a special case of SEM which is a statistical technique for testing and confirming causal relations based on data and qualitative assumptions. The dataset consists of Real Time PCR data for 84 genes relevant to the TLR signaling pathway, that were obtained from 192 patients with CLL that have been classified based on the mutational status of their clonotypic antigen receptors as mutated CLL (M-CLL) or unmutated CLL (U-CLL). The causal effects among genes were estimated through regression weights. In each case, the initially assumed model was based on the KEGG pathway database which provides reference pathways. The initial models were tested with respect to the M-CLL and U-CLL datasets. Modifications were made according to the statistical results (statistically significant regression weights, modification indices), concluding to models with good fit. Models were consistent to the reference pathway mostly for M-CLL and much less for U-CLL. These results go along with the well-described differences in immune signaling between the two subgroups, and may indicate that signaling in U-CLL is more impaired and/or modulated by complex regulatory networks that remain to be elucidated.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"13 39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114561315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antoine Lavignotte, C. Gravier, Julien Subercaze, J. Fayolle
{"title":"Quality of Experience, a Very Personal Experience!","authors":"Antoine Lavignotte, C. Gravier, Julien Subercaze, J. Fayolle","doi":"10.1109/DEXA.2013.30","DOIUrl":"https://doi.org/10.1109/DEXA.2013.30","url":null,"abstract":"At the Pervasive Computing area, end users expect to receive a multimedia service with an acceptable quality, anytime, and anywhere. Measuring this acceptability is usually referred to Quality of Experience (QoE). Unlike Quality of Service (QoS) which focuses on allocating expected systems and network resources, QoE is concerned with optimizing the perceived quality of a service by end-users. The appraisal of the user's acceptability thresholds is a key factor for service providers to perform adaptation decisions on their products (VoD, IPTV, online games, etc). While QoE is individualized, no study has yet examined to what extent. In this paper, we report an empirical study to understand if QoE should be managed globally, per cluster of users, or personally. We prove that every user has his very own vision of a same service, therefore that future QoE-based adaptive systems should take into account this property.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134002874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predicting Student Performance in Higher Education","authors":"Hana Bydzovská, L. Popelínský","doi":"10.1109/DEXA.2013.22","DOIUrl":"https://doi.org/10.1109/DEXA.2013.22","url":null,"abstract":"In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130842844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nuno Guedes, T. Pinto, Z. Vale, T. Sousa, T. Sousa
{"title":"Electricity Markets Portfolio Optimization Using a Particle Swarm Approach","authors":"Nuno Guedes, T. Pinto, Z. Vale, T. Sousa, T. Sousa","doi":"10.1109/DEXA.2013.49","DOIUrl":"https://doi.org/10.1109/DEXA.2013.49","url":null,"abstract":"Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors' research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player's portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and off-peak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator - OMIE.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"336 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122025440","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Word Semantic Similarity Based on Document's Title","authors":"Mohamed Said Hamani, R. Maamri","doi":"10.1109/DEXA.2013.12","DOIUrl":"https://doi.org/10.1109/DEXA.2013.12","url":null,"abstract":"Measuring similarity between words using a search engine based on page counts alone is a challenging task. Search engines consider a document as a bag of words, ignoring the position of words in a document. In order to measure semantic similarity between two given words, this paper proposes a transformation function for web measures along with a new approach that exploits the document's title attribute and uses page counts alone returned by Web search engines. Experimental results on benchmark datasets show that the proposed approach outperforms snippets alone methods, achieving a correlation coefficient up to 71%.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115056169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Neslihan Sirin Saygili, T. Acarman, Tassadit Amghar, B. Levrat
{"title":"Managing Genetic Algorithm Parameters to Improve SegGen -- A Thematic Segmentation Algorithm","authors":"Neslihan Sirin Saygili, T. Acarman, Tassadit Amghar, B. Levrat","doi":"10.1109/DEXA.2013.15","DOIUrl":"https://doi.org/10.1109/DEXA.2013.15","url":null,"abstract":"SegGen [1] is a linear thematic segmentation algorithm grounded on a variant of the Strength Pareto Evolutionary Algorithm [2] and aims at optimizing the two criteria of the Salton's [3] definition of segments: a segment is a part of text whose internal cohesion and dissimilarity with its adjacent segments are maximal. This paper describes improvements that have been implemented in the approach taken by SegGen by tuning the genetic algorithm parameters according with the evolution of the quality of the generated populations. Two kinds of reasons originate the tuning of the parameters and have been implemented here. First as it could be measured by the values of global criteria of the population quality, the global quality of the generated populations increases as the process goes and it seems reasonable to set values to parameters and define new operators, which favor intensification and diminish diversification factors in the search process. Second since individuals in the populations are plausible segmentations it seems reasonable to weight sentences in the current segmentation depending on their distance to the boundaries of the segment they belong to for the calculus of similarities between sentences implied in the two criteria to be optimized. Although this tuning of the parameters of the algorithm currently rests on estimations based on experiments, first results are promising.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122083150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Freitas, Seán O'Riain, E. Curry, J. F. C. Silva, Danilo S. Carvalho
{"title":"Representing Texts as Contextualized Entity-Centric Linked Data Graphs","authors":"A. Freitas, Seán O'Riain, E. Curry, J. F. C. Silva, Danilo S. Carvalho","doi":"10.1109/DEXA.2013.21","DOIUrl":"https://doi.org/10.1109/DEXA.2013.21","url":null,"abstract":"The integration of a small fraction of the information present in the Web of Documents to the Linked Data Web can provide a significant shift on the amount of information available to data consumers. However, information extracted from text does not easily fit into the usually highly normalized structure of ontology-based datasets. While the representation of structured data assumes a high level of regularity, relatively simple and consistent conceptual models, the representation of information extracted from texts need to take into account large terminological variation, complex contextual/dependency patterns, and fuzzy or conflicting semantics. This work focuses on bridging the gap between structured and unstructured data, proposing the representation of text as structured discourse graphs (SDGs), targeting an RDF representation of unstructured data. The representation focuses on a semantic best-effort information extraction scenario, where information from text is extracted under a pay-as-you-go data quality perspective, trading terminological normalization for domain-independency, context capture, wider representation scope and maximization of textual information capture.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123968686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of Protein-Protein Interaction Management Systems","authors":"A. Rapti, E. Theodoridis, A. Tsakalidis","doi":"10.1109/DEXA.2013.39","DOIUrl":"https://doi.org/10.1109/DEXA.2013.39","url":null,"abstract":"Protein-protein interactions (PPIs) are very important for observing the behavior of known proteins in biological processes and in the study of many diseases. Currently, there is a number of PPI databases publicly available in the Web. In most cases, these datasets are managed by traditional relational database management systems (RDBMS) and they are shared as plain or XML files. A very useful approach would be the the unification of these separated data sources following the Semantic Web linked open data (LOD) paradigm, in order to complement and extend the existing knowledge of each data source. Semantic representation and storage of linked open datasets can be performed by many off-the-shelf systems modeling them as Resource Description Framework (RDF) models. RDF modeling, provides great flexibility for the linking, querying and mining of various PPI data sources. In this paper, we evaluate experimentally the interconnection and storage of various PPI data sources with off-the-shelf RDF storages. We examine the performance of such storages against traditional RDBMS in the context of PPI dataset management. Our main findings show that each one of the alternative storage methods, has its own advantages and disadvantages (in processing time and memory utilization) according to various types of queries.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"461 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120849064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Linked Data Perspective for Collaboration in Mashup Development","authors":"D. Bianchini, V. D. Antonellis, M. Melchiori","doi":"10.1109/DEXA.2013.20","DOIUrl":"https://doi.org/10.1109/DEXA.2013.20","url":null,"abstract":"Web mashup is becoming an approach more and more popular for developing Web applications both for general and enterprise purposes. Mashup development is fueled by Web sites, as Programmable Web and Mashape, offering large, ever growing, catalogues of software components accessible through Web APIs. Developing Web mashup applications requires specialized knowledge about Web APIs, technologies and the way to combine them in a meaningful way. This kind of knowledge is often available but distributed among different experts. In this paper we introduce the LINKSMAN (LINKed data Supported MAshup collaboratioN) approach for expert search in enterprise mashup development. The approach is based on integrating knowledge both internal and external to enterprises. The result is then published as linked data set. We show how typical collaboration patterns among mashup developers can be formalized and implemented on this linked data set to support expert search. A prototype application is also described.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131797239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Techno-economic Balance of Load-Adaptive Telecommunication Network Operation for Energy Efficiency Improvements","authors":"C. Lange, H. Lehmann","doi":"10.1109/DEXA.2013.33","DOIUrl":"https://doi.org/10.1109/DEXA.2013.33","url":null,"abstract":"Load-adaptive telecommunication network operation has crystallized as a promising option for improving the network energy efficiency. On the one hand significant energy savings are expected when the network capacity follows the traffic load, on the other hand efforts for preparing networks for this kind of dynamic operation are necessary regarding, for example, systems and network processes. To account for all this, an energy-related and a generalized techno-economic balance is developed. Results calculated for exemplary traffic load curves and boundary conditions show that there are significant monetary benefits to be expected in particular in case of moderate validity periods of the network configurations. Furthermore, the need to evaluate the load-adaptive network operation case from a techno-economic viewpoint carefully before employing it in a particular telecommunication network becomes evident.","PeriodicalId":428515,"journal":{"name":"2013 24th International Workshop on Database and Expert Systems Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121657201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}