{"title":"Service Oriented Tools for Medical Records Management and Versioning","authors":"A. S. Ellouze, R. Bouaziz, A. Jmal","doi":"10.1109/DBKDA.2010.20","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.20","url":null,"abstract":"The technological impact of the Internet gave birth to telemedicine that provides both the digitalization of patient’s medical records, and the coordination between different healthcare actors. Work in this domain has shown that the standard XML is one of solid supports for the specification of the structure and of the semantic of clinical information, especially XML also ensures publishing medical records through Web. However, evolutions in time of XML schema of these records as well as interpenetration of temporal aspects in medical information are not sufficiently handled. In this paper, we address the problem of modeling, managing and implementing temporal medical data. We define efficient mechanisms for the management of multi-version medical records. For each structure evolution, our approach for schema versioning of XML medical records consists in creating a new schema version and in preserving old ones and their corresponding data. We present an algorithm to generate and to maintain schema versions of documents. We show the feasibility of our approach by the development of an application based on service oriented tools to publish services of versioned electronic medical records through the web.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128269253","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":"Clustering Relational Database Entities Using K-means","authors":"F. Bourennani, M. Guennoun, Ying Zhu","doi":"10.1109/DBKDA.2010.32","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.32","url":null,"abstract":"The fast evolution of hardware and the internet made large volumes of data more accessible. This data is composed of heterogeneous data types such as text, numbers, multimedia, and others. Non-overlapping research communities work on processing homogeneous data types. Nevertheless, from the user perspective, these heterogeneous data types should behave and be accessed in a similar fashion. Processing heterogeneous data types, which is Heterogeneous Data Mining (HDM), is a complex task. However, the HDM by Unified Vectorization (HDM-UV) seems to be an appropriate solution for this problem because it permits to process the heterogeneous data types simultaneously. In this paper, we use K-means and Self-Organizing Maps for simultaneously processing textual and numerical data types by UV. We evaluate how the HDM-UV improves the clustering results of these two algorithms (SOM, K-means) by comparing them to the traditional homogeneous data processing. Furthermore, we compare the clustering results of the two algorithms applied to a data integration problem.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133000142","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}
Mounir Tlili, Reza Akbarinia, Esther Pacitti, P. Valduriez
{"title":"Scalable P2P Reconciliation Infrastructure for Collaborative Text Editing","authors":"Mounir Tlili, Reza Akbarinia, Esther Pacitti, P. Valduriez","doi":"10.1109/DBKDA.2010.21","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.21","url":null,"abstract":"We address the problem of optimistic replication forcollaborative text editing in Peer-to-Peer (P2P) systems. This problem is challenging because of concurrent updating at multiple peers and dynamic behavior of peers. Operationaltransformation (OT) is a typical approach used for handlingoptimistic replication in the context of distributed text editing. However, most of OT solutions are neither scalable nor suited for P2P networks due to the dynamic behavior of peers. In this paper, we propose a scalable P2P reconciliation infrastructure for OT that assures eventual consistency and liveness despite dynamicity and failures. We propose a P2P logging and timestamping service called P2P-LTR (P2P Logging and Timestamping for Reconciliation) which exploits a distributed hash table (DHT) for reconciliation. While updating replica copies at collaborating peer editors, updates are stored in ahighly available P2P log. To enforce eventual consistency, these updates must be retrieved in a specific total order to be reconciled at the peer editors. P2P-LTR provides an efficient mechanism for determining the total order of updates. It also deals with the case of peers that may join and leave the system during the update operation. We evaluated the performance of P2P-LTR through simulation; the results show the efficiency and the scalability of our solution.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115614266","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":"SARI OpenRec -- Empowering Recommendation Systems with Business Events","authors":"Philip Limbeck, Martin Suntinger, Josef Schiefer","doi":"10.1109/DBKDA.2010.40","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.40","url":null,"abstract":"With growing product portfolios of eCommerce companies it gets increasingly challenging for customers to find the products they like best. Current recommendation approaches primarily rely on customer-product affinities derived from explicit ratings or historical purchases. In this paper, we introduce SARI OpenRec, an extendible framework combining the capabilities of complex event processing and recommendation systems. SARI OpenRec enhances recommendations by considering most recent customer activities reflected in event streams. These include website activities (e.g., page views, advertisement clicks, page durations), as well as business activities such as purchases, payments and returned goods. The integrated rule engine enables companies to model rules for dynamically adjusting the recommendation based on stock levels, seasonal factors or current marketing campaigns. Finally, we demonstrate how to analyze historic events and evaluate the recommendation process using the visualization facilities in SARI OpenRec. We claim that by considering a wide range of external signals and business events, the recommendation system becomes more context-aware and personalized.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116010980","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":"Optimistic Synchronization of Cooperative XML Authoring Using Tunable Transaction Boundaries","authors":"Francis Gropengießer, K. Sattler","doi":"10.1109/DBKDA.2010.10","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.10","url":null,"abstract":"Design applications, e.g., CAD or media production, often require multiple users to work cooperatively on shared data, e.g., XML documents. Using explicit transactions in such environments is difficult, because designers usually do not want to consider transactions or ACID. However, applying transactions in order to control visibility of changes or specify recovery units, is reasonable, but determining transaction boundaries must be transparent for the designer. For this reason we propose a novel approach for the automatic determination of transaction boundaries which considers the degree of cooperation designers want to achieve. Furthermore, we present an optimistic synchronization model based on the traditional backward oriented concurrency control (BOCC) algorithm, in order to synchronize the determined transactions in multi-user environments. It exploits the semantics of tree operations on XML data and enforces a correctness criterion weaker than serializability. As our evaluation shows, when multiple users work cooperatively on shared data, this model significantly reduces the number of transaction aborts in comparison to the traditional BOCC approach.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130727486","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}
Martin Suntinger, Hannes Obweger, Josef Schiefer, Philip Limbeck, G. Raidl
{"title":"Trend-Based Similarity Search in Time-Series Data","authors":"Martin Suntinger, Hannes Obweger, Josef Schiefer, Philip Limbeck, G. Raidl","doi":"10.1109/DBKDA.2010.33","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.33","url":null,"abstract":"In this paper, we present a novel approach towards time-series similarity search. Our technique relies on trends in a curve’s movement over time. A trend is characterized by a series’, values channeling in a certain direction (up, down, sideways) over a given time period before changing direction. We extract trend-turning points and utilize them for computing the similarity of two series based on the slopes between their turning points. For the turning point extraction, well-known techniques from financial market analysis are applied. The method supports queries of variable lengths and is resistant to different scaling of query and candidate sequence. It supports both subsequence searching and full sequence matching. One particular focus of this work is to enable simple modeling of query patterns as well as efficient similarity score updates in case of appending new data points.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128442274","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}
Nils Grimsmo, T. A. Bjørklund, Øystein Torbjørnsen
{"title":"XLeaf: Twig Evaluation with Skipping Loop Joins and Virtual Nodes","authors":"Nils Grimsmo, T. A. Bjørklund, Øystein Torbjørnsen","doi":"10.1109/DBKDA.2010.8","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.8","url":null,"abstract":"XML indexing and search has become an important topic, and twig joins are key building blocks in XML search systems. This paper describes a novel approach using a nested loop twig join algorithm, which combines several existing techniques to speed up evaluation of XML queries. We combine structural summaries, path indexing and prefix path partitioning to reduce the amount of data read by the join. This effect is amplified by only reading data for leaf query nodes, and inferring data for internal nodes from the structural summary. Skipping is used to speed up merges where query leaves have differing selectivity. Multiple access methods are implemented as materialized views instead of succinct secondary indexes for better locality. This redundancy is made affordable in terms of space by using compression in a back-end with columnar storage. We have implemented an experimental prototype, which shows a speedup of two orders of magnitude on XPath queries with value predicates, when compared to existing open source and commercial systems using a subset of the techniques. Space usage is also improved.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130100872","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":"Implementing Optimistic Concurrency Control for Persistence Middleware Using Row Version Verification","authors":"M. Laiho, F. Laux","doi":"10.1109/DBKDA.2010.25","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.25","url":null,"abstract":"Modern web-based applications are often built as multi-tier architecture using persistence middleware. Middleware technology providers recommend the use of Optimistic Concurrency Control (OCC) mechanism to avoid the risk of blocked resources. However, most vendors of relational database management systems implement only locking schemes for concurrency control. As consequence a kind of OCC has to be implemented at client or middleware side. A simple Row Version Verification (RVV) mechanism has been proposed to implement an OCC at client side. %The implementation of RVV depends on the underlying database management system and the specifics of the middleware. For performance reasons the middleware uses buffers (cache) of its own to avoid network traffic and possible disk I/O. This caching however complicates the use of RVV because the data in the middleware cache may be stale (outdated). We investigate various data access technologies, including the new Java Persistence API (JPA) and Microsoft's LINQ technologies for their ability to use the RVV programming discipline. The use of persistence middleware that tries to relieve the programmer from the low level transaction programming turns out to even complicate the situation in some cases. Programmed examples show how to use SQL data access patterns to solve the problem.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126720763","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":"Discovering Informative Syntactic Relationships between Named Entities in Biomedical Literature","authors":"A. Appice, Michelangelo Ceci, Corrado Loglisci","doi":"10.1109/DBKDA.2010.14","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.14","url":null,"abstract":"The discovery of new and potentially meaningful relationships between named entities in biomedical literature can take great advantage from the application of multirelational data mining approaches in text mining. This is motivated by the peculiarity of multi-relational data mining to be able to express and manipulate relationships between entities. We investigate the application of such an approach to address the task of identifying informative syntactic structures, which are frequent in biomedical abstract corpora. Initially, named entities are annotated in text corpora according to some biomedical dictionary (e.g. MeSH taxonomy). Tagged entities are then integrated in syntactic structures with the role of subject and/or object of the corresponding verb. These structures are represented in a first-order language. Multi-relational approach to frequent pattern discovery allows to identify the verb-based relationships between the named entities which frequently occur in the corpora. Preliminary experiments with a collection of abstracts obtained by querying Medline on a specific disease are reported.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130547832","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":"Optimized Representation for Classifying Qualitative Data","authors":"M. Cadot, A. Lelu","doi":"10.1109/DBKDA.2010.26","DOIUrl":"https://doi.org/10.1109/DBKDA.2010.26","url":null,"abstract":"Extracting knowledge out of qualitative data is an ever-growing issue in our networking world. Opposite to the widespread trend consisting of extending general classification methods to zero/one-valued qualitative variables, we explore here another path: we first build a specific representation for these data, respectful of the non-occurrence as well as presence of an item, and making the interactions between variables explicit. Combinatorics considerations in our Midova expansion method limit the proliferation of itemsets when building level k+1 on level k, and limit the maximal level K. We validate our approach on three of the public access datasets of University of California, Irvine, repository: our generalization accuracy is equal or better than the best reported one, to our knowledge, on Breast Cancer and TicTacToe datasets, honorable on Monks-2 near-parity problem.","PeriodicalId":273177,"journal":{"name":"2010 Second International Conference on Advances in Databases, Knowledge, and Data Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132779933","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}