The book is composed of two main parts. The first part is a general study of Semantic Web Search. The second part specifically focuses on the use of semantics throughout the search process, compiling a big picture of Process-oriented Semantic Web Search from different pieces of work that target specific aspects of the process. In particular, this book provides a rigorous account of the concepts and technologies proposed for searching resources and semantic data on the Semantic Web. To collate the various approaches and to better understand what the notion of Semantic Web Search entails, this book presents a general Semantic Web Search model. With respect to this model, the book provides a comprehensive discussion of the state-of-the-art. It elaborates on approaches for crawling, managing and searching Semantic Web resources as well as the various schemes proposed for ranking search results. Besides these specific approaches, search is also studied in a general multi-data source scenario. This shall demonstrate how this work on search is extended and applied to the Web setting.
A major feature of the book is that it considers search and the use of semantics for search also from a process point of view. Extending the general model, the book introduces the notion of Process-oriented Semantic Web Search, where semantics is exploited throughout the entire search process – from query construction to query processing up to result presentation and query refinement. Specific pieces of work targeting these individual steps of the process are combined to form a coherent and consistent picture of Process-oriented Semantic Web Search. In order to convey this general notion as well as the specific concepts and technologies developed for supporting the search process, this book presents a compilation of work called SemSearchPro and provides detailed descriptions on the underlying approaches.
In this book, we elaborate on the concepts, objectives, problems, and challenges of searching on the Semantic Web generally called Semantic Web Search. Based on a general search model, we compare different concepts that exist in literature. Specifically, the concept of data retrieval can be distinguished from the one of document retrieval. Independent of the search tasks and the items to be retrieved, there is one paradigm called Semantic Search, which is centered on the use of semantics. Semantic Web Search is considered as a special kind of Semantic Search, which is focused on the task of data retrieval on the Semantic Web. The main objective of Semantic Web Search is to address more complex information needs. This breaks down to delivering more relevant results to more complex queries, which might range from precise answers in the form of facts, to complex results in the form of entities and their relations, up to integrated units of content that combine heterogeneous data from different sources on the Web. Challenges to this end include dealing with the large and increasing volume of data on the Semantic Web, its heterogeneity as well as its complexity. In fact, complexity in this scenario has many facets. From the system point of view, complexity poses additional requirements for data management and processing. But also, complexity imposes an additional burden on the user. An effective Semantic Web Search solution must be not only efficient, scalable and deliver high quality results but also, the users must be able to exploit it.
We discuss the state of the art of Semantic Web Search and in this context, position the specific contributions we made in this work. These contributions are integrated to form a holistic Process-oriented Semantic Web Search approach called SemSearchPro, one of the first solution towards large-scale Semantic Web Search, and the first one of its kind that does not entirely focus on the main search task of matching queries against system resources but actually considers the entire search process. While SemSearchPro also aims at dealing with the main challenges of data volume, heterogeneity and complexity, it also considers the complexity users have to deal with. Its supports go beyond query processing to include additional steps of the search process – from query construction to query refinement up to result presentation and exploration – in order to facilitate users in dealing with complex information needs, queries, and results on the Semantic Web.
This book focuses on SemSearchPro and the research contributions made to realize this Process-oriented Semantic Web Search approach.
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