International Journal of Research and Review www.ijrrjournal.com E-ISSN: 2349-9788; P-ISSN: 2454-2237

Review Paper

An Overview of Semantic Search Engines

Subham Roy, Akshay Modak, Debabrata Barik, Surajit Goon

Department of Computer Application, Eminent College of Management & Technology, Barasat, Kolkata, West Bengal 700126, India

Corresponding Author: Debabrata Barik

ABSTRACT

Semantic Search is a search technique that improves searching precision by understanding the purpose of the search and the contextual significance of words as they appear in the searchable data space, whether on the web to generate more relevant result. We highlight here about Semantic Search, and discuss about different type of Semantic and differences between keyword base search and Semantic Search and the advantage of Semantic Search. We also give a brief overview of the history of semantic search and its feature scope in the world.

Keywords: Semantic Search, Semantic Wed, Semantic search engine

INTRODUCTION concept mapping, graph patterns, and The word "Semantic" refers to the blurred logic. meaning or summary of something. Web search is a major Web "Semantics", applied to search, essentially technology that was initially based on a refers to the study of words and its logic. It combination of textual keyword search and is a technique of data searching, but it is not document ranking depending on the Web's only a search query to find keywords, but connection structure. That's why it has many also to determine the intent and contextual constraints, and there are plenty of study meaning of the search words that a person operations toward smarter web searching, uses. Therefore, it provides more significant called Semantic Web search, which is search results by assessing and presently one of the hottest study subjects in understanding the search phrase and both Semantic Web and Web search. [2] discovering the most appropriate results in a Search engine has become a primary website, or any other data store. It need to explore the . Without Search operates on linguistic semantics principles. Engine, there are no uses of information in [1] Unlike typical search algorithms, website, blog, etc., because without search semantic searching is based on the searched engine, it is almost impossible to look for phrase's context, substance, intent and one by one website just for search concept of the searched phrase. As part of information in internet. Semantics is the the search, semantic search also organizes study with meaning. It focuses on the place, term synonyms, present trends, word meaningful relationship, such as words, variants and other natural language sentences, signs, and symbols. The term was components. Semantic search ideas are coined by the inventor of the World Wide obtained from different search algorithms Web, Tim Berners-Lee, who defined it as "a and methodologies, including keyword-to- data web that can be processed by machines directly and indirectly". [3]

International Journal of Research & Review (www.ijrrjournal.com) 73 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

computer or search engine cannot (unless tags are intentionally placed). This is because HTML is intended to store visual information and is not written in a language of programming. [6]

COMPARISON OVER KEYWORD BASED SEARCH Similar search queries are typed in both search engines such as Google as a keyword search engine and Hakia as a Figure 1: Sematic Search Process Semantic Search engine to compare The searching process of Semantic keyword and semantic search engine. But Search is divided into five processes as fundamental search results are provided by shown in Figure 1. In the first step the user the engine. It does not give entered the searching element in the search us a precise and meaningful result. It is the bar. In the next step the search engine drawback of Keyword Search Engine. In analyzed the search items. In the third step contrast, using Semantic based search the analyzed data is matched with a engine, most appropriate and precise query thesaurus. Then semantic search accesses outcomes are obtained. That means the matched data and then semantic search traditional search engines generate results of engine returns the relevant content. a specified query within a specified framework, but Semantic search engines HISTORY OF SEMANTIC SEARCH operate on a Semantic based strategy that is helpful for precise and meaningful query Semantic is the study and mining of [7] language. It was first used by French data. philologist Michel Bréal in 1983. It is used In Keyword Search, the obtained to define how the words can be different data depends on keywords and page ranking meanings for distinct individuals because of algorithms that can yield spam outcomes their experiential backgrounds. For without using any methodology and does example, French, Dutch, or Hindi, any not emphasis on stop words like is, or, and, language can be a natural language, it can how because it does not give exact results be an artificial language, such as a what user is looking for. It shows all web programming language for PCs. In 1967, pages which may or may not fulfill the Robert-Floyd wrote a paper describing the request of the user and it is a challenging use of language Semantics in computers and job to select appropriate page from many received credit for starting the programming pages. Keyword Search Engine does not language Semantics field, and his work emphasize any words or sentences that are included the analysis and design of helpful in responding to precise outcomes. It algorithms used to locate the most efficient uses HTML, XML language for creation of paths in a network, quantile calculation, . programming language parsing, and But in Semantic Search, the information sorting. [4,5] The featured article retrieved information is independent of 'The Semantic Web' was released by James keywords and page rank algorithms that Hendler, , and Tim Berners-Lee generate exact results rather than any in May, 2001.Their paper described a new insignificant results. It utilizes ontology to way to use and to search the Internet, an establish keyword relationships and takes on added dimension with full of new stop words and punctuation marks because possibilities. Although the text of an HTML each and every tiny character is taken into web page can be read by a human, but a consideration as it impacts search outcomes.

International Journal of Research & Review (www.ijrrjournal.com) 74 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

[7] It shows only those results that will metadata. [8] Metadata means data about any answer our query so it does not highlight other data in a compiled manner. The user any words or phrases which are useful in gets the information about any specific answering getting accurate results. It uses information sequentially or separately. It’s Semantic Web languages like XML, OIL, not smart process. The primary objective of DAML+OIL, DAML-S, OWL, RDF, meta data is to search, but it can also be WSDL, URI, UDDI for creation of used for another objective.

Search result of Keyword Search Engine:

Figure 2: Keyword Search Engine

Search result of Semantic Search Engine:

Figure 3: Semantic Search Engine

DIFFERENT TYPES OF SEMANTIC essential capability of hakia engine is that it SEARCH projects results using equivalent terms. The Hakia: Hakia is a semantic search engine search items are divided into Web, News, that delivers appropriate outcomes depend Blogs, video and can be arranged by on matching idea instead of matching relevance or date. Hakia’s semantic search keywords or prevalence ranking. The engine is consist of three technologies. OntoSem prompts not only keywords to enter- but a (sense repository) is a lexical database query, a phrasing, or a sentence. They cater where words are classified into the diverse search results based on meaning and not on “senses” they impart. QDEX (Query the popularity of search terms. A very indexing technique) evokes all queries

International Journal of Research & Review (www.ijrrjournal.com) 75 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

concerning the content. Semantic Rank reliable sites in less time compare to algorithm independently orders content. It Keyword Search Engine. [9] gives almost exact results collected from

Kngine: Kngine is a smart engine that answers de facto questions commonly posed and carries out actions. Kngine recognizes what users are truly looking for and delivers significant outcomes to them. You can speak or type your question for Kngine. It extracts the factual data from each phrase to build / update our knowledge graph. Kngine results are based either on web results or on image result. In order to achieve state-of - the-art accuracy, Kngine also uses the power of deep learning, big data and unsupervised learning. It learns and improves all the time. Currently, it includes over eight million Concepts where the power of the site resides. [10,11]

Kosmix: Kosmix is acts as guide to Web. It allows users to browse the Web topic wise and to present a dashboard of appropriate Videos, Images, News, Opinions, Blogs, Forums, Twitter, Amazon, Facebook and references to related topics. The categorization engine of Kosmix arranges the Internet into pages of magazine-style based on the topic. It also uses Deep Web. [12,13]

International Journal of Research & Review (www.ijrrjournal.com) 76 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

DuckDuckGo: If you use Google, forget it, because unlike Google, DuckDuckGo is a feature- rich Semantic Search Engine. If you search for a term that has more than one meaning, with its disambiguation results, you will be able to select what you originally searching for. For example, if you browse for the term Orange, it will give list of possible meanings including fruit, online reservation system, corporate site, business service, etc. [13]

Powerset: In Sep 2005, the firm introduced with the aim of making search easier and more intuitive. Later, Microsoft acquired it on July 1, 2008. It concentrates on doing just a single thing and doing it really well by using natural language processing to understand the nature of the question and return pages containing the answer. It comprises all the search results from Wikipedia, using semantics Search terms can be articulated as questions, which will be answered, or as simple terms, and results will be accumulated from all the significant pages on Wikipedia from different resources. [14,15]

International Journal of Research & Review (www.ijrrjournal.com) 77 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

Sensebot: Sensebot utilizes to analyze web pages and recognize important semantic ideas. It then conducts a multi-document overview of content to generate a consistent overview which, depending on the query provided, gives a summarized precise search outcome. The synopsis gives A nice concept of the subject of the query. [15] The overview can be read and is consistent. It saves time. To get the outcomes, the user does not need to go through many web pages. The search engine itself attempts to comprehend the query idea, in fact what it includes and provides a suitable outcome. [16]

Cognition: Cognition finds meaning formula in the quest. It provides Link results. It is a search engine that provides the ability to learn about various elements of distinct languages and promotes Ontology, Morphology, and Synonyms. The use of this technology could vary from better enterprise-wide search to more appropriate advertising. It offers access to this technology with APIs. [17]

International Journal of Research & Review (www.ijrrjournal.com) 78 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

Swoogle: A crawler-based indexing and retrieval Semantic Web. It analyzes the documents it has found in order to calculate beneficial metadata characteristics and their relationships. [18] Identified documents are likewise recorded by a data recovery framework which can utilize either character N-Gram or URIrefs as keywords to search specific documents and to figure out similarities among number of documents. [19] By using text-mining and multi-records summarization, it extracts meaning from web pages. It finds the semantic web's suitable ontology and instance data structure. [20]

Factbites: Factbites searches for material that is factual and accurate. To abstract meaning from web pages, it utilizes text mining and multi-record summarization. [21] The outcome provides us a feeling of carefully and precisely understanding stuff. It is best to filter out those non-relevant sites. [22]

International Journal of Research & Review (www.ijrrjournal.com) 79 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

COMPARISON OF DIFFERENT SEMANTIC SEARCH ENGINES

The following Table 3 shows the comparison of different Semantic Search Engine.

Name Features Search Result Type of Search Results Result Multilingual Advantages Methodology Summary Result Explanation

Hakia Excellent Pure content The content It leads to The outcomes Yes Yes It easily collects summaries, related analysis. of the Link & Free of the search information searches, algorithm documents is Text are divided into appropriate to our of semantic rank, important Web, News, query from CMR Blog, Videos various reliable sites. It identifies Focus and Saves time information Kngine It answers de facto It uses the It extracts It also results web results or Yes Yes You can speak or questions power of deep the factual in a image result type your commonly posed learning, big data from summary question for and carries out data and each phrase form Kngine actions, it learns unsupervised to build / and improves all the learning update our time knowledge graph Kosmix It has features such Classification In Search It provides Amazon, No Yes It organizes its as Digg, Buzz, of contents Query, it the results of Facebook, user's internet Flikr, Fark, and gives the search Video, outcomes Youtube on its first significance. Websites, page. Article of the News, Blog, function of the Images, Forums image DuckDuckGo Emphasizes It is a Meta Gives user It results in a Images, local Yes Yes It accumulates privacy, it does not search engine query text / summary search, self- results from monitor private data capable of content- form suggestions, various sources of the user, it results collecting data related news, weather, like Yahoo and in the use of other from other results cooking recipes Wikipedia, etc. sources or search search engines etc. engines including its own Powerset It helps to search It uses natural Multiple web It provides results are Yes Yes results in more easy language pages Link results gathered from It concentrates on and intuitive way processing to generate a all the doing just a understand the text significant single thing and nature of the overview pages on doing it really question and Wikipedia from well by return pages different accumulating containing the resources search results answer from various sources. Sensebot It provides To abstract Multiple web It results in a Summary of all Yes Yes It provides us a overview in the meaning from pages summary web pages on summary of the result of search webpages, it generate a form our subject outcomes rather query, text mining, utilizes text text than all multi-document mining and overview connections summary rather multi-record associated with than links to other summarization our question website pages. It discovers top search results and then summarizes this information Cognition It is a linguistic Processing of Retrieves the It provides It allows 4 Yes Yes It is a search search engine that natural search Link results. domains for engine that uses Ontology, languages meaning searching: Law, allows us to learn Synonyms and formula. Medicine, about various Morphology Wiki, Bible elements of distinct languages and promotes ontology, morphology and synonyms Swoogle It offers various Indexes records Gives It provides O Online No No It discovers the search services that use RDF outcomes WL, RDF re ontology, suitable ontology using the REST from the sults Documents, and instance of interface semantic Terms, the semantic

International Journal of Research & Review (www.ijrrjournal.com) 80 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

web Published web- web's data based data structure Factbites Search for questions Searches for To abstract It provides Coherent Yes No The outcome and answers, search authentic and meaning results that phrases and provides us a for dictionaries, informative from web are connections feeling of authentic and material pages, it summarized, carefully and relevant search / utilizes text oriented and precisely content mining and appealing understanding multi-record stuff. It is best to summarizati filter out those on non-relevant sites

STATISTICAL ANALYSIS results out of ten were listed individually for A Semantic Search Engine, namely, each search engine as shown in Table 2. DuckDuckGo and a Keyword based Search Engine, namely, Google were selected to RESULT compare the search results. Subsequently, In our study, it was seen that relevant five topics which consist of one or two document searched by DuckDuckGo is terms and five natural language queries more (76 out of 100) than Google. Figure 4 were randomly chosen as shown in Table 1. depict the mean precision ratio of search Then, the first ten results of searched engine for first 10 results and Figure 5 queries were assessed and the relevant represent no of related document searched based on given topics.

Table 1: Query List Table 2: No of related document searched

Figure 4: mean precision ratio of search engine Figure 5: no of related document searched for 10 topics

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MAJOR ADVANTAGES OF iv. Whenever you're happy with SEMANTIC SEARCH anything, try throwing in some i. The main advantage originates in the related words, for example-If you're extra semantic relationships that reading a Panda bear article, you're search engines deliver better results likely to find words like "Bamboo, during query routing. These China, Animal and Mammal" in that relationships offer a more dynamic, particular article. If you can identify communicative and dialog-based the right words and include them in result pages or SERPs. Semantic your search engine, transmit the search technologies enable subject of your content and thereby individuals to monitor information promote visibility. [26] by idea rather than by a defined v. The technique of using a semantic match of keyword or key phrase. strategy and structured information This implies that people can for content planning uses a data differentiate more easily what's model to characterize the going to be on a page while information. Jarno van Driel focuses choosing which one to click to. on the importance and authority of Search engines have everything to using structured information for do with what the user wants. The company intelligence and provides semantic strategy is more effective case studies and how-to. Read proof in ensuring that people do not that this approach benefits locations become dissatisfied after turning up that incorporate semantic somewhere SERPs recommend. [23] advantages. Semantic information ii. Semantic search takes user intent produces data recovery a and user data into account. Google's progressively beneficial procedure. machine-learning algorithm has vi. How Internet users find the content trained itself to interpret what you they want is dynamically advancing really want based on the aggregate towards a semantic “shape” to reach data of millions of searches. Perhaps that data. One way to clarify it is that this is the most important thing the natural ordering and logic of web about searching semantic. The best data has a semantic reason and job. results are not those with lots of Business owners now have more keywords, an optimized H1, and a capacity to customize and control well-designed title tag. [24] the text copy of your digital content. iii. A rich not only vii. Organized information may look to recovers query-related documents, the human eye like a lot of mixed but also information that is words, but for search engines, it conceptually similar. Where explains the words on a page. In the keyword and statistical technologies task of sorting out data, it is basic for for higher precision use synonyms GoogleBot to discover mechanisms and other techniques and recall to more precisely understand a web research approach results in more page’s content. By becoming more false results and errors. The idea like authentic learning machines, behind the technology enabled by search engines are interpreting semantic overcomes these content much quicker and more difficulties because, through the precisely. These new advances offer strength of a semantic network, it colossal advantage for search eliminates the ambiguities that get capacities to be robust in terms of the real meaning of the terms. [25] scalability, efficiency, and resilience to failure from indiscernible search

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queries. So, by using schematics, we promising research issues are how to make this easier for them. [27] automatically translate natural language queries into formal ontological queries, and SOME CONTROVERSIES how to automatically add semantic REGARDING SEMANTIC SEARCH annotations to Web content, or alternatively ENGINES how to automatically extract knowledge i. The findings are sometimes incorrect from Web content. Another central research and repeated over and over again. issue in semantic Web search is how to ii. Identification of intention in such create and maintain the underlying search engines is very important ontologies and a closely related important iii. The user could enter the worldwide research challenge is the evolution and web at the beginning, i.e. they updating of and mapping between the provided the choice of ontologies that are underlying Semantic disambiguation. [28] Web Search, where it is similarly desirable iv. Some of the smart semantic search to have a very high degree of automation. A engines that do not demonstrate the further important issue is how to consider significance of accuracy and recall. implicit and explicit contextual information Google is not a semantic search to adapt the search results to the needs of engine, but elevated accuracy and the users. Performing Web search through low recall. [29] returning simple answers to simple v. Usually the knowledge specific to questions in natural language is still science the domain of the user. Users may fiction, not to mention performing Web not define all possibilities but the search in the form of query answering query's synonyms and variants have relative to some concrete domain or even an issue that consumers are not sure general query answering. A number of how to use Phrase. [30] future directions need to consider for this vi. Trillions of information on the work. So, it will be the most important and subject-based search was distributed powerful search technique in the world in to the only to future. The improvements suggested to be extract the subject information in made in the future indicate the development pages and produce an outcome for of such an effective search engine search the user. But if we go for search technology that is able to meet the engines based on semantic, it can difficulties effectively and is compatible create several choices for the with worldwide web technology standards. keyword of the individual user. The metadata key-based search for the REFERENCES processing of web pages is not 1. Guha, R., McCool, R., & Miller, E. (2003, adequate for the individual Crawler. May). Semantic search. In Proceedings of [31] the 12th international conference on World Wide Web (pp. 700-709). ACM.

2. Fazzinga, B., & Lukasiewicz, T. (2010). CONCLUSION Semantic search on the Web. Semantic This paper concludes an overview of Web, 1(1, 2), 89-96. Semantic Search, Semantic Web and 3. Jayavel, S., Anouncia, M., & Kapoor, A. different Semantic Search Engines and (2013). Semantic Search Engine. advantages of Semantic Search. This paper International Journal of Recent gives a brief overview of comparison of Contributions from Engineering, Science & different Semantic Search Engine so that IT (iJES), 1(2), 19-21. anyone can do a further research on it. We 4. Berners-Lee, T. (1998, September). get to know that it is the best and hottest Semantic Web Road map. Retrieved from research topic and some of the most https://www.w3.org/DesignIssues/Semantic. html

International Journal of Research & Review (www.ijrrjournal.com) 83 Vol.6; Issue: 10; October 2019 Subham Roy et.al. An Overview of Semantic Search Engines

5. Manjula, D., & Geetha, T. V. (2004). 17. Kassim, J. M., & Rahmany, M. (2009, Semantic search engine. Journal of August). Introduction to semantic search Information & Knowledge engine. In 2009 International Conference on Management, 3(01), 107-117. Electrical Engineering and 6. Foote, K. D. (2016, May 9). A Brief History Informatics (Vol. 2, pp. 380-386). IEEE. of Semantics. Retrieved from 18. Renteria-Agualimpia, W., López-Pellicer, F. https://www.dataversity.net/brief-history- J., Muro-Medrano, P. R., Nogueras-Iso, J., semantics/ & Zarazaga-Soria, F. J. (2010). Exploring 7. Malve, A., & Chawan, P. (2015). A the advances in semantic search engines. Comparative Study of Keyword and In Distributed Computing and Artificial Semantic based Search Intelligence (pp. 613-620). Springer, Berlin, Engine. International Journal of Innovative Heidelberg. Research in Science, Engineering and 19. Ding, L., Finin, T., Joshi, A., Pan, R., Cost, Technology, 4(11), 11156-11161. R. S., Peng, Y., ... & Sachs, J. (2004, 8. Arroyo, S., Ding, Y., Lara, R., Stollberg, November). Swoogle: a search and metadata M., & Fensel, D. (2004, March). Semantic engine for the semantic web. In Proceedings web languages. strengths and weakness. of the thirteenth ACM international In International Conference in Applied conference on Information and knowledge computing (IADIS04) (pp. 23-26). management (pp. 652-659). ACM. 9. Sudeepthi, G., Anuradha, G., & Babu, M. S. 20. Rashid, J., & Nisar, M. W. (2016). A Study P. (2012). A survey on semantic web search on Semantic Searching, Semantic Search engine. International Journal of Computer Engines and Technologies Used for Science Issues (IJCSI), 9(2), 241. Semantic Search Engines. International 10. Kngine. (n.d.). Retrieved from Journal of Information Technology and https://www.crunchbase.com/organization/k Computer Science (IJITCS), 8(10), 82-89. ngine 21. FactBites : The Results in Meaningful 11. Khan, J. A., Sangroha, D., Ahmad, M., & Sentences. (2007, August 27). Retrieved Rahman, M. T. (2014, November). A from performance evaluation of semantic based https://www.searchenginejournal.com/factbi search engines and keyword based search tes-the-results-in-meaningful- engines. In 2014 International Conference sentences/5553/ on Medical Imaging, m-Health and 22. Renteria-Agualimpia, W., López-Pellicer, F. Emerging Communication Systems J., Muro-Medrano, P. R., Nogueras-Iso, J., (MedCom) (pp. 168-173). IEEE. & Zarazaga-Soria, F. J. (2010). Exploring 12. Kosmix. (n.d.). Retrieved from the advances in semantic search engines. https://www.crunchbase.com/organization/k In Distributed Computing and Artificial osmix#section-overview Intelligence (Vol. 79, pp. 613-620). 13. Rashid, J., & Nisar, M. W. (2016). A Study Springer, Berlin, Heidelberg. on Semantic Searching, Semantic Search 23. Jeannie Hill. (2016, April 16). 6 Benefits Engines and Technologies Used for That Semantic Search Brings to Digital Semantic Search Engines. International Marketing. Retrieved from Journal of Information Technology and https://www.hillwebcreations.com/benefits- Computer Science (IJITCS), 8(10), 82-89. semantic-search-brings-digital-marketing/ 14. Powerset. (n.d.). Retrieved from 24. Everything You Need To Know About https://www.crunchbase.com/organization/p Semantic Search And What It Means for owerset Your Website. (2017, July 15). Retrieved 15. Sudeepthi, G., Anuradha, G., & Babu, M. S. from P. (2012). A survey on semantic web search https://www.crazyegg.com/blog/everything- engine. International Journal of Computer about-semantic-search/ Science Issues (IJCSI), 9(2), 241. 25. Advantages of Semantic Search | Omneek. 16. Sheth, A., Bertram, C., Avant, D., (n.d.). Retrieved from Hammond, B., Kochut, K., & Warke, Y. https://www.omneek.com/en/resources/adva (2002). Managing semantic content for the ntages-of-semantic-search/ Web. IEEE Internet computing, 6(4), 80-87. 26. Semantic Search: What Is It And How Can You Benefit From It? (2018, January 24).

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Retrieved from search engine based on expressive https://www.imarkinfotech.com/semantic- semantics. In Proceedings of the 13th search-can-benefit/ international World Wide Web conference 27. Taibi, D., Gentile, M., & Seta, L. (2005). A on Alternate track papers & posters (pp. semantic search engine for learning 472-473). ACM. resources. In Third International 30. Lee, C. H., & Liu, A. (2005, July). Toward Conference on Multimedia and Information intention aware & Communication Technologies in systems. In 2005 IEEE International Education. Conference on Services Computing 28. Madhu, G., Govardhan, D. A., & (SCC'05) Vol-1 (Vol. 1, pp. 69-76). IEEE. Rajinikanth, D. T. (2011). Intelligent 31. Jenice Aroma, R., & Kurian, M. (2012). A semantic web search engines: a brief Survey on need for Semantic web. survey. arXiv preprint arXiv:1102.0831. International Journal of Scientific Research 29. Ding, D., Yang, J., Li, Q., Wang, L., & and Publications. Wenyin, L. (2004, May). Towards a flash

How to cite this article: Roy S, Modak A, Barik D et.al. An overview of semantic search engines. International Journal of Research and Review. 2019; 6(10):73-85.

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