Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> The most widely accepted defining feature of the semantic web is machine-usable content. By this definition, the semantic web is already manifest in shopping agents that automatically access and use web content to find the lowest air fares or book prices. However, where are the semantics? Most people regard the semantic web as a vision, not a reality--so shopping agents should not "count." To use web content, machines need to know what to do when they encounter it, which, in turn, requires the machine to know what the content means (that is, its semantics). The challenge of developing the semantic web is how to put this knowledge into the machine. The manner in which it is done is at the heart of the confusion about the semantic web. The goal of this article is to clear up some of this confusion.I explain that shopping agents work in the complete absence of any explicit account of the semantics of web content because the meaning of the web content that the agents are expected to encounter can be determined by the human programmers who hardwire it into the web application software. I therefore regard shopping agents as a degenerate case of the semantic web. I note various shortcomings of this approach. I conclude by presenting some ideas about how the semantic web will likely evolve. <s> BIB001 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> In our paper we present the intermediate results of a project aiming at the creation of a knowledge-based infrastructure for search and navigation in audiovisual repositories. The approach is based on highly automated media processing and is therefore specifically targeted to historically grown archives (broadcasters, universities, public and corporate media archives, etc.) lacking the time and/or the financial means to manually annotate their digital media assets. In the project a conceptual architecture was developed to meet the requirements of a set of knowledge-intensive user scenarios for the utilization of rich media content in the B2B and B2C areas. Pluggable RDF knowledge components act as a link between a semantic indexing and knowledge-based navigation. <s> BIB002 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> A fundamental principle for reusing software assets is providing means to access them. Information retrieval mechanisms assisted by semantic initiatives, play a very important role in finding relevant reusable assets. In this context, this paper presents a semantic search tool in order to improve the precision of search returns. Furthermore, the requirements, the decomposition of architectural module and aspects of implementation are presented. <s> BIB003 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Distributed repositories, containing digital documents are usually maintained and managed independently according to organization/users own requirements. Same information (i.e. documents containing same information) in different repositories, may be represented differently, makes it hard to retrieve desired information. Keyword based information retrieval technique helps in improving recall of user query result, but having low precision. To improve precision, we adopt semantic information retrieval technique. We are proposing architecture for semantic based information retrieval, in which plain text is read semantically and the extracted metadata is stored and later used for semantic search. <s> BIB004 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> While semantic search technologies have been proven to work well in specific domains, they still have to confront two main challenges to scale up to the Web in its entirety. In this work we address this issue with a novel semantic search system that a) provides the user with the capability to query Semantic Web information using natural language, by means of an ontology-based Question Answering (QA) system [14] and b) complements the specific answers retrieved during the QA process with a ranked list of documents from the Web [3]. Our results show that ontology-based semantic search capabilities can be used to complement and enhance keyword search technologies. <s> BIB005 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> There is a need for specialized search engines focused on specific disciplines that can use domain knowledge to guide the user to find exactly the resources they are searching for. In addition, these engines should be able search multiple and heterogeneous resource catalogs simultaneously and aggregate results from these catalogs. Noesis, a customizable search engine with semantic and resource aggregation capabilities is presented in this paper. The Noesis architecture has been designed to be modular, allowing it to be adapted by projects in different disciplines. This paper describes the Noesis architecture, highlights its application in several projects, and presents a user scenario for one of the projects is presented in this paper. <s> BIB006 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Finding relevant information on the Web can be a complex task for most of the users. Although Web search applications are improving, they still need to be more intelligent to adapt to the search domain targeted by users, the evolution of this domain and users' characteristics. In this paper, we present an experimental assessment of the TARGET framework for improving the relevance of the documents when users are searching the Web by using adaptive ontologies. This is done first by introducing the TARGET approach. We will briefly present the used ontologies and their ability to adapt to domain evolution. Then, We detail the TARGET tool used in our experimentations. This includes its architecture, its ability to carry out the ontology adaptation process as well as the way it searches the Web and ranks the returned results. Finally, we discuss the results obtained using the tool through the presentation of our case study devoted to the retrieval of scientific articles. <s> BIB007 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> The provision of accurate, comprehensive and condensed information contained in distributed environmental information systems via public search interfaces raises several technological challenges. Our approach to tackle these challenges is based on a consequent use of ontologies. Starting with an analysis of requirements resulting from semantic search scenarios, we explain the advantages of using ontologies based on standards and aim to reuse and transform terminological systems available in the environmental domain into ontologies. We develop an architecture guided by the premise of exerting a minimum of influence on existing search infrastructures. As a consequence of using a (possibly large) number of ontologies, tools for ontology management are needed. A key argument for using ontologies is that nowadays – as an outcome of the Semantic Web initiative - very powerful processing tools are available. We elaborate ontology mapping as an example and outline how a comprehensive ontology management can be achieved. <s> BIB008 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> We present an architecture aimed at semantic search and synthesis of information acquired from the document repositories. The proposed framework is expected to provide domain knowledge interfaces enabling the internally implemented algorithms to identify relationships between documents, researchers, institutions, as well as concepts extracted from various types of knowledge bases. The framework should be scalable with respect to data volumes, diversity of analytic processes, and the speed of search. In this paper, we investigate these requirements for the case of medical publications gathered in PubMed. <s> BIB009 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Children with pervasive developmental disorders have special needs so they should be supported with special education programs. These programs are planned according to the type and degree of the disorder, age, characteristics, and needs of the children. Families prefer Internet to search resources about related educational methods (and associated activity/game) and materials. However, syntactic search in today's Internet is insufficient because of its static base and the search results are not sufficient enough to offer desired relevant results corresponding to a child's needs. With the help of Semantic Web-based agents an intelligent system able to identify the suitable educational methods and material, will contribute to the development of children with disorders, and support education specialists in this process. In addition it will be extremely useful for the families of these children in need of assisting and monitoring their child's development. In this article, an Educational Activity Finder (EAF) is being proposed. The architecture of EAF is structured after semantic Web technology so that it can find and propose semantically relevant suitable educational methods (i.e., activities to carry out) and material for use by children with disorders. The knowledge base of EAF keeps educational methods using the OWL language. All related concepts, attributes, and relations between these concepts and features about pervasive developmental disorders are defined through ontology. EAF is structured to recognize a pervasive developmental disorder, sort out symptoms and anomalies, suggest activities, compile performance scores, and decide on new activity based on user preferences by utilizing the semantic descriptions of available methods and activities. Strength of EAF is demonstrated through sample scenarios. EAF may be used by parents, pre-school educators, primary schools, special educational institutions and experts working for these institutions, university students studying in related fields, and individuals interested in pervasive developmental disorders. <s> BIB010 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Human musculoskeletal system resources of the human body are valuable for the learning and medical purposes. Internet-based information from conventional search engines such as Google or Yahoo cannot response to the need of useful, accurate, reliable and good-quality human musculoskeletal resources related to medical processes, pathological knowledge and practical expertise. In this present work, an advanced knowledge-based personalized search engine was developed. Our search engine was based on a client-server multi-layer multi-agent architecture and the principle of semantic web services to acquire dynamically accurate and reliable HMSR information by a semantic processing and visualization approach. A security-enhanced mechanism was applied to protect the medical information. A multi-agent crawler was implemented to develop a content-based database of HMSR information. A new semantic-based PageRank score with related mathematical formulas were also defined and implemented. As the results, semantic web service descriptions were presented in OWL, WSDL and OWL-S formats. Operational scenarios with related web-based interfaces for personal computers and mobile devices were presented and analyzed. Functional comparison between our knowledge-based search engine, a conventional search engine and a semantic search engine showed the originality and the robustness of our knowledge-based personalized search engine. In fact, our knowledge-based personalized search engine allows different users such as orthopedic patient and experts or healthcare system managers or medical students to access remotely into useful, accurate, reliable and good-quality HMSR information for their learning and medical purposes. <s> BIB011 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> The amount of information on health subjects on the Web and users' interest in having efficient access to it continues to increase. This information can also be very useful for professionals, researchers and students in this field. But the usual word-based search does not allow full exploration of the information, pointing to the need for more semantic approaches. Aiming to contribute to providing a semantic search for information on Health, available using written Portuguese, the article presents enhanced search platform architecture based on the enterprise search platform (FAST), providing a processing pipeline capable of exploring annotation of entities and relations defined in a domain. A modular architecture was defined in which an ontology-based knowledge base has an essential role. As it is essential to make the user task as simple as possible, the platform also includes ontology navigation in the classes and relations of the entity to guide queries; use of the most frequent domain classes in the documents relating to a search to provide additional ways of navigation; and inclusion in the score of the ontology-guided annotations. As a first proof of concept, the architecture was instantiated in a specific domain, neurological diseases, for which an ontology was created. <s> BIB012 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Semantic modelling provides a potential basis for interoperating among different systems and applications in the Internet of Things (IoT). However, current work has mostly focused on IoT resource management while not on the access and utilisation of information generated by the ``Things''. We present the design of a comprehensive and lightweight semantic description model for knowledge representation in the IoT domain. The design follows the widely recognised best practices in knowledge engineering and ontology modelling. Users are allowed to extend the model by linking to external ontologies, knowledge bases or existing linked data. Scalable access to IoT services and resources is achieved through a distributed, semantic storage design. The usefulness of the model is also illustrated through an IoT service discovery method. <s> BIB013 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <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> BIB014 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <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> BIB015 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> In this paper we present a novel report search engine which uses a dedicated ontology, employs natural language processing and acts as a recommender system. The work on the project has been financed by QUESTOR [1], an Eureka project. The aim of the project was to create an innovative product that will be used in large companies to lower the complexities in the report management workflow. The stated purpose was to be able to query the report management system in natural language, for example entering the question ”Give the situation of the procurements in the surgery department in May 2011”. When entering the question in the graphical user interface, the user is guided by contextual suggestions. The final question is analyzed using natural language processing and transformed in a semantic query language, SPARQL, that is executed on a metadata semantic repository. There, all the reports were indexed, using a domain specific ontology. In the first step all the matching reports are retrieved, the parameters are detected from the question and completed as values for the retrieved reports. Then the list of results is passed through a ranker, which orders the results based on their similarity score with the question. The rank of the chosen result is increased to favor that result in subsequent queries. QUESTOR also introduced a new feature: ad-hoc queries. If the question contains more parameters than there are available in the results, a new report is made in real time, using data from the metadata repository and from the report database. This feature was introduced during the development, at the request of the stakeholders. The paper is organized in the following way: a state of the art of the domain, the Questor architecture and algorithms, experimental data and conclusions. <s> BIB016 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> Ever since the introduction of the service oriented model of computing (SOA), service discovery has been the major research challenge in SOA. Service consumers usually prefer to express their requirements informally. Expressing requirements in such a way leads to difficulties in the matching procedure, and hence results in poor matching results. In this paper, we present the concept of multi-level search as a solution for matching informal expression of user requirements. In the suggested approach, intermediate brokers receive service requests and suggest suitable services that match the given requests. We present a mechanism by which an intelligent broker utilizes a knowledge based system to overcome the drawbacks of syntactic and semantic discovery. The intelligent broker receives informal user requirements and performs multi-level search. The search starts with key word search, then meaning search, and finally expert search. If the keyword search fails to produce a proper matching, then, the search progresses to the following levels: semantic, and then intelligent search. In this paper we argue that multi-level search could revive the dream of automatic service discovery and present a detailed model for implementation. <s> BIB017 </s> Research on proposals and trends in the architectures of semantic search engines: A systematic literature review <s> 2) RQ2: Evaluation methods for validating and/or verifying the architecture of a semantic search engine: <s> In this paper we present an architecture and approach to publishing open linked data in the cultural heritage domain. We demonstrate our approach for building a system both for data publishing and consumption and show how user benefits can be achieved with semantic technologies. For domain knowledge representation the CIDOC-CRM ontology is used. As a main source of trusted data, we use the data of the web portal of the Russian Museum. For data enrichment we selected DBpedia and the published Linked Data of the British Museum. The evaluation shows the potential of semantic applications for data publishing in contextual environment, semantic search, visualization and automated enrichment according to needs and expectations of art experts and regular museum visitors. <s> BIB018
The aim of this research question is to identify what evaluation methods exist for validating and verifying an architecture. In this case, validation is related to whether the system fulfills its requirements; verification is related to whether the system was developed right  . For this question, two fields were proposed in order to retrieve the data from the studies: a Verification method: this field aims to get any verification method proposed by the study. b Validation method: this field aims to get any validation method proposed by the study. For this research question unfortunately there was no study found that fulfilled the search criteria and the quality assessment checklist. Even though there was no study identified, it can be said that not finding studies for this research question constitutes an opportunity for a future work. This is discussed further in the conclusions. 3) RQ3: Requirements an architecture of a semantic search engine complies with: The aim of this research question is to identify what kind of requirements an architecture needs to comply with. Although requirements are closed to the field or domain where the semantic search engine is working, the purpose of this research question is to identify any common underlying requirement that an architecture of a semantic search engine needs to fulfill independent of that field or domain. For this question, one field was proposed in order to retrieve the data from the studies: a Requirements: this field aims to get the list of requirements that the architecture of a semantic search engines needs to comply with. The requirements or needs were identified from the study, whether they were explicitly or implicitly mentioned. This field is meant to gather both functional and nonfunctional requirements. This was done this way in order to understand the requirements in their context, and taking into account that usually requirements are not classified and presented in these two categories. That implied to read the full text of the selected studies thoroughly. There are 18 studies found to answer this question. The following is a set of common requirements identified from those studies: a Precision on results, mentioned by BIB003 , BIB004 , BIB014 ,  , and in some way it is also mentioned by BIB017 , BIB011 ,  ,  . This requirement is related to find the most relevant results based on the user's search query. The purpose of the semantic search is to improve results based on the user's intention and the context of the search query, so it does not come as a surprise that an architecture of a semantic search engine must have precision on results as one of its requirements. b Existence and maintenance of ontologies, mentioned by BIB003 ,  . Although this is explicitly mentioned by few articles, it has a great impact because of the important role that ontologies play in an architecture (as it is described in subsection VI-B4). Almost all selected studies rely on ontologies to make the search engine work. Ontologies are the base to learn new concepts, share knowledge and make possible that search agents can retrieve information even when new concepts were not previously defined BIB001 . c Usability, mentioned by BIB003 , BIB010 ,  , BIB018 . This is concerned with how user-friendly users find the search engine, how easy it is to use and if it is accessible through common ways, such as smartphones and tablets. In the case of BIB018 , richer representation takes a special meaning because of data the search engines needs to display, i.e. Russian museum art collections. d Evolution of knowledge base as new documents appears, mentioned by BIB004 ,  . This is pretty close to the previous ontology-related requirement, as knowledge and ontologies are related. In this case, a knowledge base needs to accept new concepts as new information becomes available. In the case of BIB002 , it is even proposed that the system should be able to cover various domain models. e Handle structured, unstructured and heterogeneous data sources, mentioned by BIB004 , BIB014 ,  , BIB008 , BIB009 , BIB018 . This requirement is related to the diverse sources a semantic search needs to deal with. As shown in the work of Fernandez et al. BIB005 , heterogeneous sources, heterogeneous knowledge bases and heterogeneous ontologies can help getting answers for natural language queries, which are used in BIB009 . For structured and unstructured data, such as what we can find in the Web, crawlers and annotation mechanisms help coping with those, so semantic search can be done on those kinds of data BIB005 . f Use of ontologies for suggesting or guiding the user search, mentioned by BIB012 , BIB007 , BIB006 , BIB011 , BIB015 ,  ,  . This requirement is about having the help of ontologies while the user writes his/her query. This help can be presented as suggestions of additional or related terms BIB006 , or it can use user's preferences in order to retrieve relevant results, as proposed by  or BIB007 . g Use of natural language, mentioned by BIB016 , BIB017 , BIB009 . This requirement is related to the usage of natural language queries that can express users' intentions in a much freer way. This implies that the search engine needs to process and translate the user's query properly, using techniques such as word-sense disambiguation. Then the query can be consumed by the domain ontologies so a match can be found against the knowledge base. h Handle large amount of data, mentioned by BIB009 . This requirement, although mentioned by one study, is worth to be pointed out because new search engines will need to have a broader action range, such as in the Internet of Things as proposed in the work of Wang et al. BIB013 . However, the search engine proposed byŚlȩzak et al. is oriented to the biomedical literature field, which is small when compared to other broader Internet-based solutions. It is worth mentioning that, although is not stated literally on the previous requirements identified from the studies, for BIB002 having a decoupled system is important, as it keeps the engine core independent from the data and knowledge layers.