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"Topics covered include skyline queries, probabilistic logics and reasoning, theory of conceptual modeling, prediction in networks of moving objects, validation of XML integrity constraints, management of loosely structured multi-dimensional data, data discovery in the presence of annotations, and quality ranking for Web articles."

"The LNCS journal Transactions on large-scale data- and knowledge-centered systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the seventh issue of transactions on large-scale data- and knowledge-centered systems, contains five revised selected regular papers on the following topics: data management, data streams, service-oriented computing, abstract algebraic frameworks, RDF and ontologies, and conceptual model frameworks."

"The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between Grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This, the fifth issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains nine selected full-length papers, focusing on the topics of query processing, information extraction, management of dataspaces and contents, and mobile applications."

"This two volume set LNCS 7446 and LNCS 7447 constitutes the refereed proceedings of the 23rd International Conference on Database and Expert Systems Applications, DEXA 2012, held in Vienna, Austria, September 3-6, 2012. The 49 revised full papers presented together with 37 short papers and 2 keynote talks were carefully reviewed and selected from 179 submissions. These papers discuss a range of topics including, database query processing, in particular XML queries, labelling of XML documents, computational efficiency, data extraction, personalization, preferences, and ranking, security and privacy, database schema evaluation and evolution, semantic web, privacy and provenance, data mining, data streaming, distributed systems, searching and query answering, structuring, compression and optimization, failure, fault analysis, and uncertainty, predication, extraction, and annotation, ranking and personalisation, database partitioning and performance measurement, recommendation and prediction systems, business processes, and social networking."

"This two volume set LNCS 7446 and LNCS 7447 constitutes the refereed proceedings of the 23rd International Conference on Database and Expert Systems Applications, DEXA 2012, held in Vienna, Austria, September 3-6, 2012. The 49 revised full papers presented together with 37 short papers and 2 keynote talks were carefully reviewed and selected from 179 submissions. These papers discuss a range of topics including, database query processing, in particular XML queries, labelling of XML documents, computational efficiency, data extraction, personalization, preferences, and ranking, security and privacy, database schema evaluation and evolution, semantic web, privacy and provenance, data mining, data streaming, distributed systems, searching and query answering, structuring, compression and optimization, failure, fault analysis, and uncertainty, predication, extraction, and annotation, ranking and personalisation, database partitioning and performance measurement, recommendation and prediction systems, business processes, and social networking."

"Untuk mengambil mata kuliah bare, seorang mahasiswa akan selalu meminta informasi mengenai mata kullah yang akan diambil. Informasi yang diperoleh pun beragam, terutama dalam hal yang berhubungan dengan tingkat kesulitan mata kuliah. Tingkat kesulitan mata kuliah dapat tergantung dari beberapa faktor seperti kondisl akademis mahasiswa yang bersangkutan (dalam hal ini Indeks Prestasi), nilai mata kuliah prasyarat clan minat. Hal-hal demikian sangat subyektif clan berbecla untuk setiap individu mahasiswa. Namun di samping itu juga terdapat hal-hal obyektif untuk mengukur tingkat kesulitan suatu mata kuliah seperti besar SKS, banyaknya tugas-tugas pendukung clan jumlah maters yang diajarkan. Sistem pakar berbasis data dapat digunakan untuk menggambarkan hal-hal tersebut di atas (yang bersifat subyektif maupun obyektif) dengan memanfaatkan data akademis mahasiswa clan data mata kuliah serta menggabungkannya sehingga dapat menggambarkan tingkat kesulitan suatu mata kuliah mendekati keadaan yang sesungguhnya. Pada skripsi ini akan dibuat suatu model aplikasi perangkat lunak sistem pakar berbasis data untuk memberikan gambaran mengenai tingkat kesulitan mata kuliah berdasarkan data akademis individu mahasiswa clan data mengenai mata kuliah, sehingga untuk keperluan konsultasi akademis akan sangat membantu mahasiswa clan dosen wall dalam proses pengisian Formulir Rencana Studi (FRS)."