Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> Abstract To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse—definitions of classes, relations, functions, and other objects—is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms. <s> BIB001 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> Abstract : Architectural decisions have a great impact on the consequent quality of software systems. As a result, it is important to evaluate how a software architecture meets its quality demands. Though much focus has been placed on modeling and describing the software architecture as a design artifact, we found that relatively little is known about the current experience with software architecture evaluation. This report details the results of two workshops on software architecture evaluation, held at the Software Engineering Institute (SEI) on November 9-10, 1995 and May 9-10,1996. The purpose of the workshops was to determine the state of industrial practice in the evaluation of software architectures with respect to a set of desired quality attributes, and to uncover recommendations for best practices. In this report, we summarize the findings of the two workshops, define a set of dimensions to characterize various software architecture evaluation techniques, and make concrete recommendations for implementing architecture evaluation practices. <s> BIB002 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> This paper addresses the role of case-based reasoning in semantic search, and in particular, as it applies to Knowledge Sifter, an agent-based ontology-driven search system based on Web services. The Knowledge Sifter architecture is extended to include a case-based methodology for collaborative semantic search, including case creation, indexing and retrieval services. A collaborative filtering methodology is presented that uses stored cases as a way to improve user query specification, refinement and processing. <s> BIB003 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> Digital ecosystem (DE) is comprised of heterogeneous and distributed species which can play the dual role of service provider and service requester. Nowadays, DE lacks semantic search support, which means it cannot provide a reliable and trustworthy link between service providers and service requesters. To solve this issue, we design a conceptual framework of a service-ontology-based semantic service search engine. Apart from the function of service search with a novel search model, this framework also provides a quality-of-services-based service evaluation and ranking methodology. To evaluate the feasibility of our framework, we implement a prototype in the transport service domain, and compare the performance of the search model with three traditional information retrieval models. The conclusion to this evaluation and suggestions for future works are provided in the final section. <s> BIB004 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> Due to the increased amount of available biodiversity data, many biodiversity research institutions are now making their databases openly available on the web. Researchers in the field use this databases to extract new knowledge and also share their own discoveries. However, when these researchers need to find relevant information in the data, they still rely on the traditional search approach, based on text matching, that is not appropriate to be used in these large amounts of heterogeneous biodiversity's data, leading to search results with low precision and recall. We present a new architecture that tackle this problem using a semantic search system for biodiversity data. Semantic search aims to improve search accuracy by using ontologies to understand user objectives and the contextual meaning of terms used in the search to generate more relevant results. Biodiversity data is mapped to terms from relevant ontologies, such as Darwin Core, DBpedia, Ontobio and Catalogue of Life, stored using semantic web formats and queried using semantic web tools (such as triple stores). A prototype semantic search tool was successfully implemented and evaluated by users from the National Research Institute for the Amazon (INPA). Our results show that the semantic search approach has a better precision (28% improvement) and recall (25% improvement) when compared to keyword based search, when used in a big set of representative biodiversity data (206,000 records) from INPA and the Emilio Gueldi Museum in Para (MPEG). We also show that, because the biodiversity data is now in semantic web format and mapped to ontology terms, it is easy to enhance it with information from other sources, an example using deforestation data (from the National Institute of Space Research - INPE) to enrich collection data is shown. <s> BIB005 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> VII. CONCLUSIONS AND FUTURE WORK <s> Abstract The current web IR system retrieves relevant information only based on the keywords which is inadequate for that vast amount of data. It provides limited capabilities to capture the concepts of the user needs and the relation between the keywords. These limitations lead to the idea of the user conceptual search which includes concepts and meanings. This study deals with the Semantic Based Information Retrieval System for a semantic web search and presented with an improved algorithm to retrieve the information in a more efficient way. This architecture takes as input a list of plain keywords provided by the user and the query is converted into semantic query. This conversion is carried out with the help of the domain concepts of the pre-existing domain ontologies and a third party thesaurus and discover semantic relationship between them in runtime. The relevant information for the semantic query is retrieved and ranked according to the relevancy with the help of an improved algorithm. The performance analysis shows that the proposed system can improve the accuracy and effectiveness for retrieving relevant web documents compared to the existing systems. <s> BIB006
The goal of this review is to identify how the architectures of semantic search engines work, how the proposals are designed and what problems they were and are solving. Most of the studies, as depicted previously, propose a concrete implementation for their architectures, so those systems were and are working now in a myriad of application fields. As there was no previous study that summarized this subject, no time range filter was set when searching for the studies. It can be seen that most of the studies try to propose a solution for a previous unresolved problem, to design a new alternative for users, or to improve search results. To measure whether those proposals represent an improvement, some studies present comparison results or performance benchmarks as is the case of the work of Amanqui et al. BIB005 , Thangaraj and Sujatha BIB006 or Dong et al. BIB004 . However, as the purpose of this systematic review is not related to that kind of experiments, this can be considered as a good starting point for a future work. As for the modules that a semantic search engine comprises, it can be said that reasoning components such as ontologies and inference engines constitute key modules present across the studies. Domain ontologies in particular are a fundamental piece in a semantic search engine as they allow addressing the needs of a specific domain and user requirements BIB003 . The use of ontologies fosters reusability, as new concepts are identified and added to the ontology, making its maintenance crucial as it evolves over time  . Likewise, it was identified that ontologies and knowledge play together a key role in the architectures reviewed. One of the key roles for knowledge is knowledge sharing that is achievable through the implementation of the ontologies that search engines rely on BIB001 . This brings benefits to search results, improving search engines' precision and recall which, along with usability and the ability to handle unstructured and heterogeneous sources, constitutes some of the most important requirements that the architecture of a semantic search engine needs to fulfill as it is designed and developed. Finally, although there was no validation and verification methods identified for the architectures of semantic search engines, this can be seen as an opportunity for future work by proposing validation and verification mechanisms already in use in other software engineering application fields. As mentioned by Abowd et al. in BIB002 , there are many benefits of architectural evaluation methods, such as a better understanding and documentation of the system, clarification and prioritization of requirements, and early detection of problems in the architecture, which boosts architecture quality.