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"In this book, the editors present an overall overview and comparison of the main current evaluation initiatives for SWS. The presentation is divided into four parts, each referring to one of the evaluation initiatives. Part I covers the long-established first two tracks of the Semantic Service Selection (S3) Contest – the OWL-S matchmaker evaluation and the SAWSDL matchmaker evaluation. Part II introduces the new S3 Jena Geography Dataset (JGD) cross evaluation contest. Part III presents the semantic web service challenge. Lastly, Part IV reports on the semantic aspects of the web service challenge. The introduction to each part provides an overview of the evaluation initiative and overall results for its latest evaluation workshops. The following chapters in each part, written by the participants, detail their approaches, solutions and lessons learned."

"Agent-based semantic web service composition closely examines the various aspects of SWS composition, and explores the concept that a multi-agent system can serve as an SWS composition system in which its agents can interact with one another to satisfy a high-level goal. In addition to surveying various proposed multi-agent-based SWS composition models, the book also highlights the cognitive parameter-based semantic web service selection models that can be used in multi-agent-based SWS composition, and outlines a new negotiation agreement-based SWS composition that can outperform existing techniques. Agent-based semantic web service composition is intended for researchers and practitioners as a reference guide for optimizing SWS composition and implementing multi-agent systems. Instructors and other academics working in a related field will also find the book invaluable."

""Semantic Web models and technologies provide information in machine-readable languages that enable computers to access the Web more intelligently and perform tasks automatically without the direction of users. These technologies are relatively recent and advancing rapidly, creating a set of unique challenges for those developing applications. Semantic Web for the Working Ontologist is the essential, comprehensive resource on semantic modeling, for practitioners in health care, artificial intelligence, finance, engineering, military intelligence, enterprise architecture, and more. Focused on developing useful and reusable models, this market-leading book explains how to build semantic content (ontologies) and how to build applications that access that content"--Provided by publisher."

"Salah satu tantangan bagi pengembangan teknologi e-learning selanjutnya adalah mengembangkan sistem pembelajaran yang memiliki fitur personalisasi sesuai dengan kondisi setiap pembelajarnya. Untuk itu diperlukan sistem yang dapat mengerti data informasi mengenai pembelajar dan kemudian menyajikan materi pembelajaran yang cocok dengan pembelajar tersebut.Penelitian di Fasilkom UI mengembangkan sistem personalized e-learning yang melakukan personalisasi berdasarkan gaya belajar (learning style) dan performa pembelajaran yang sudah dilakukannya (pre-knowledge). Selain itu sistem personalized e-learning ini juga dapat merekomendasikan mata kuliah yang cocok sesuai karakteristik pembelajar. Untuk melakukan penelitian ini digunakan teknologi Semantic Web.Salah satu komponen inti dari teknologi semantic web adalah penggunaan ontologi sebagai format struktur data. Salah satu ontologi penting yang digunakan untuk membangun personalized e-learning adalah ontologi user-model. Ontologi usermodel digunakan untuk memodelkan pengguna sistem personalized e-learning.Penelitian yang dilakukan penulis ini adalah merancang suatu ontologi user-model untuk pengembangan sistem personalized e-learning sekaligus melakukan observasi terhadap teknologi Semantic Web khususnya mengenai ontologi.

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Next challenge of e-learning development is developing learning sysrem which have personalisation feature based on the condition of every learner. It is needed the system that able to understand information data about a learner and then gives suitable learning materials for the learner.At Fasilkom UI, it is developed the personalization e-learning system which doing personalization based on learning style and learning performance. Beside that, this system also can recommend courses that suitable for characteristics of learner. Semantic Web technology is being used for this research.One of the main component of semantic web technology is usage of ontology for data structure format. One important ontology used for developing personalized e-learning is user-model ontology. User-model ontology is used for modelling a user of personalized e-learning.The research that being done by writer in is desingning an user-model ontology for personalized elearning develoment and also doing observation about semantic web technology, especially about ontology."

"Salah satu tolak ukur yang paling mudah dilihat dari pembelajaran adalah dengan performa yang ditunjukan terhadap suatu konsep tertentu. Hal itu juga berlaku dalam ELearning, setiap pembelajar akan menghasilkan performa terhadap suatu konsep yang dipelajari. Pembelajaran pada E-Learning akan lebih efektif dengan menggunakan personalisasi karena setiap pembelajar akan mendapatkan materi sesuai dengan karakteristiknya.Pada penelitian ini personalisasi dilakukan menggunakan teknologi Semantic Web yaitu ontologi, dalam hal ini ontologi yang dibahas adalah ontologi Learning Performance yang menyimpan nilai performa dari pembelajaran suatu konsep tertentu. Penelitian ini bertujuan untuk merancang ontologi Learning Performance untuk personalisasi E-Learning kemudian melakukan visualisasi menggunakan software portal. Visualisasi menggunakan portal dilakukan agar data lebih mudah dipahami.

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One of assessment of learning that can be easily seen by using performance that is shown for certain concept. This is also happen in E-Learning, every learner will show result for certain concept they have learned. Learning will be more effective if using personalization, because learner can get study material that was match with their learning characteristic.In this research, personalization is doing by using ontology, more specificly Learning Performance ontology that keep performance value from learning some concept. This research aim for design Learning Performance ontology for ELearning personalization then to visualize with software portal. Visualization using portal is in order that data can be easier to understand."

"Setiap pembelajar memiliki karakteristik berbeda-beda antara lain berupa gaya belajar, prior knowledge, dan kecerdasan. Permasalahan ini sulit sekali diakomodasi pembelajaran tradisional. Berawal dari e-commerce, personalisasi meluas ke berbagai bidang TI termasuk pembelajaran online. Teknologi untuk personalisasi salah satunya adalah semantic web yang dapat membuat sistem menjadi adaptif. Tahap awal dalam pengembangan sistem berbasis semantic web adalah pemodelan dengan ontologi yang memiliki kemampuan reasoning terhadap banyak data. Salah satu ontologi yang harus dikembangkan adalah student model ontology yang dikembangkan pada penelitian ini dengan mempertimbangkan aspek gaya belajar dan performa sebagai representasi prior knowledge dan kecerdasan siswa.

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Each learner has different characteristics including learning styles, prior knowledge, and intelligence. This problem is very difficult to accommodate by traditional learning. Starting from e-commerce field, personalization extends to various fields of IT including online learning. One of technologies for personalization is semantic web which makes systems adaptive. The first stage is modeling with ontology that has ability of reasoning large of data. One of the ontologies that must be developed is student model ontology, which is developed by considering learning styles and performance aspect that represents students prior knowledge and intelligence."

"Saat ini, Internet telah banyak digunakan untuk bertukar informasi. Sayangnya, terdapat kendala bahasa yang membuat tidak semua informasi di Internet dapat dimengerti. Telah banyak language service yang dikembangkan tetapi masih banyak kendala yang ditemui, baik dari sisi biaya hingga sisi hak cipta. Oleh karena itu, proyek Language Grid didirikan dengan harapan dapat mengatasi kendala bahasa yang ada. Language Grid adalah sebuah infrastuktur bahasa yang dibangun di Internet. Language Grid memanfaatkan teknologi web service yang memungkinkan language service yang ada di dalamnya dapat diakses dengan mudah melalui web.Dalam penelitian ini, akan dikembangkan sebuah web service yang memberikan layanan analisis morfologi bahasa Indonesia menggunakan program Morphological Analyzer yang telah dikembangkan sebelumnya oleh Femphy Pisceldo (Pisceldo, 2008). Langkah lebih lanjut adalah mengembangkan wrapper yang menggunakan teknologi web service agar layanan ini dapat diakses melalui infrastruktur Language Grid. Perancangan dari web service ini meliputi perancangan web application pada server side yang berkomunikasi langsung dengan program Morphological Analyzer, dan perancangan file WSDL yang mendefinisikan layanan yang disediakan. Selain itu, juga dilakukan perancangan web application pada client side untuk melakukan uji coba dari web service yang dihasilkan.Pada akhirnya, web service yang menyediakan layanan analisis morfologi ini berhasil dibuat, namun belum dilakukan deployment ke dalam infrastruktur Language Grid karena kendala teknis dan keterbatasan waktu pengembangan. Web service yang dihasilkan juga telah diuji coba dan telah sukses melewati uji coba tersebut.

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Nowadays, many people use Internet for sharing information. Though, there is a language barrier that prevent some of those information to be understood. Many language services have been developed, but there is still many problems to be faced (i.e. the budget and the copyright restriction). In order to conquer the language barrier over the Internet, the Language Grid project is proposed. Language Grid is a language infrastructure over the Internet. Language Grid use the web service technology which allow the language service inside it can be accessed easily via web.In this research, a web service which serve the morphological analysis in Indonesian Language, with the use of Morphological Analyzer program which is developed recently by Femphy Pisceldo (Pisceldo, 2008), will be developed. The next step is to develop the wrapper which uses web service technology, in order to make this service available on Language Grid. The design of this web service cover the design of the application on the server side which communicates directly to the Morphological Analyzer program and the design of WSDL file which defines the service. Beside those, there will also be designed an application on client side in order to test the web service developed.At last, this web service, which serve the morphological analysis in Indonesian Language, has been developed successfully. However, this web service is yet to be deployed to Language Grid, because of the limitation of the develop."