Building lightweight semantic search engines

Despite significant advances in methods for processing large volumes of structured and unstructured data, surprisingly little attention has been devoted to developing general practical methodologies that leverage state-of-the-art technologies to build domain-specific semantic search engines tailored to use cases where they could provide substantial benefits. This paper presents a methodology for developing these kinds of systems in a lightweight, modular, and flexible way with a particular focus on providing powerful search tools in domains where non-expert users encounter challenges in exploring the data repository at hand. Using an academic expertise finder tool as a case study, we demonstrate how this methodology allows us to leverage powerful off-the-shelf technology to enable the rapid, low-cost development of semantic search engines, while also affording developers with the necessary flexibility to embed user-centric design in their development in order to maximise uptake and application value.Postprin

Semantic Search and Social-Semantic Search as Cooperative Approach

Social and semantic web can be combined for searching web resources. A semantic search engine can find accurate results and annotate web resources using this cooperative approach.As the volume of information is growing, the syntactically correct outputs given by traditional search engines for the user queries have enlarged directly. In order to find exact answers for user queries many more Semantic Search Engines (SSE) are developed now a day. The Semantic Search Engines use a wide range of methods for matching the semantics behind user queries and the indexed collection of resources. The survey shows the semantic search engines domain, and presents a miscellaneous of perspectives about the different classification of approaches. A comparative scheme is presented here and the prevalent research directions in SSE with the advancements in it are identified for the efficient searching techniques

On the Precision of Search Engines: Results from a Controlled Experiment

Handling the growing amount of digital information is one of the major challenges when dealing with the World Wide Web (WWW). In particular, users crave for an effective and efficient retrieval of needed information. In this context, search engines adopt a key role. Besides conventional search engines such as Google, semantic search engines have emerged as an alternative approach in recent years. The quality of search results delivered by search engines is in influenced by many criteria. This paper picks up one specific issue, the precision, and investigates and compares the precision of current both conventional (i.e., non-semantic) and semantic search engines based on a controlled experiment with 77 participants. Specifically, Google, AltaVista, MetaGer, Hakia, Kngine, and WolframAlpha are investigated and compared

Folks Thesauri or Search Thesauri: Why Semantic Search Engines Need Folks Thesauri?

The term ‘folks thesaurus’ was coined as a combination of ‘folks’ and ‘thesaurus’. A folks thesaurus puts terms into context by defining a variety of semantic relationships among the thesaurus terms. The objective of this study is to propose and present a conceptual basis from which it will be possible to build a folks thesaurus. The folks thesaurus takes its terminology and usage from a variety of sources (e.g., users' search queries, traditional thesauri, Wikipedia categories, folksonomies, social tagging, hashtags, and log file analysis of search engines). Folks thesaurus describing subject content can play a vital role in supporting web indexing and information retrieval. Folks thesauri are useful in bridging the gap that exists between the concepts presented by authors and the conceptual terms presented by a user/searcher. Folks thesaurus limits the terms available and increases the possibility that the query will use appropriate terms. If the folks thesaurus has structure in the form of associative or hierarchical tree structure and semantic relationships such as broader terms (BT), narrower terms (NT) or related terms (RT), these may also help the user in navigation through hierarchical semantic relationships and finding an appropriate query expression. If a query is too inclusive, then narrower terms may be substituted to refine the query. On the other hand, a query returning too few results can be broadened through the substitution of broader terms. Related terms may also be an aid in navigation and query construction

Museum Collections and the Semantic Web

The paper discusses some current trends in the area of development and use of semantic portals for accessing heterogeneous museum collections on the Semantic Web. The presentation is focused on some issues concerning metadata standards for museums, museum collections ontologies and semantic search engines. A number of design considerations and recommendations are formulated.The Fourth International Conference on Digital Presentation and Preservation of Cultural and Scientific Heritage—DiPP2014 is supported by the Ministry of Education and Science and is under the patronage of UNESCO