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Architecture of Hakia Search Engine a. Crawler: Hakia forms a collection of relevant document from credible site recommended by librarian. It also crawl dynamic content from Blogs, news, database etc. b. QDexing: After collecting data from different segments, QDex(stands for Query Detection & Extraction) analyzes each web page and extracts all the possible queries that can be asked to that page by decomposing sentences into sequences of words resulting generating the vast number of queries.
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Information Retrieval has become the buzzword in the today’s era of advanced computing. The tremendous amount of information is available over the Internet in the form of documents which can either be structured or unstructured. It is really difficult to retrieve relevant information from such large pool. The traditional search engines based on key...
Semantic Search is a search technique that improves looking precision through perception the reason of the search and the contextual magnitude of phrases as they show up in the searchable statistics space, whether or not on the net to generate greater applicable result. We spotlight right here about Semantic Search, Semantic Web and talk about abou...
Search is one of the key functionalities in digital platforms and applications such as an electronic dictionary, a search engine, and an e-commerce platform. While the search function in some languages is trivial, Khmer word search is challenging given its complex writing system. Multiple orders of characters and different spelling realizations of...
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... The authors state that Google has the best performance, followed by Yahoo and Bing, respectively. Hussan [48] and Jain et al. [49] survey semanticbased search engines and point out their pros and cons. The authors state that all the surveyed semantic search engines use mainly semantic web technologies. ...
... There are several semantic search engines developed from the need for efficient, accurate, and scalable search on the web, e.g., some instances of semantic search engines include Kosmix, Kngine, Hakia, Cognition, Falcons, Lexxe, Scarlet, Sindice, Swoogle, SWSE (Semantic Web Search Engine), and Watson [49,52,53], while all these semantic search engines are developed following specific use cases and are based on different assumptions, a mutual understanding of the model that relates them to each other exists. For instance, (a) semantic web documents discovery, (b) indexing, (c) analysis, and (d) interface are the components of Swoogle [54], (a) Resource Description Framework (RDF) crawler, (b) document analysis, (c) vocabulary identification, reasoning, and indexing, (d) summarization, and (d) interface are modules of Falcon [55], and (a) Crawler, (b) Query detection and extraction, (c) ontology analysis, (d) query indexing, (e) query processor, (f) ranking, and (g) interface are components of Hakia [49]. ...
... There are several semantic search engines developed from the need for efficient, accurate, and scalable search on the web, e.g., some instances of semantic search engines include Kosmix, Kngine, Hakia, Cognition, Falcons, Lexxe, Scarlet, Sindice, Swoogle, SWSE (Semantic Web Search Engine), and Watson [49,52,53], while all these semantic search engines are developed following specific use cases and are based on different assumptions, a mutual understanding of the model that relates them to each other exists. For instance, (a) semantic web documents discovery, (b) indexing, (c) analysis, and (d) interface are the components of Swoogle [54], (a) Resource Description Framework (RDF) crawler, (b) document analysis, (c) vocabulary identification, reasoning, and indexing, (d) summarization, and (d) interface are modules of Falcon [55], and (a) Crawler, (b) Query detection and extraction, (c) ontology analysis, (d) query indexing, (e) query processor, (f) ranking, and (g) interface are components of Hakia [49]. ...
Search on the web, specifically fetching of the relevant content, has been paid attention to since the advent of the web and particularly in recent years due to the tremendous growth in the volume of data and web pages. This paper categorizes the search services from the early days of the web to the present into keyword search engines, semantic search engines, question answering systems, dialogue systems and chatbots. As the first generation of search engines, keyword search engines have adopted keyword-based techniques to find the web pages containing the query keywords and ranking search results. In contrast, semantic search engines try to find meaningful and accurate results on the meaning and relations of things. Question-answering systems aim to find precise answers to natural language questions rather than returning a ranked list of relevant sources. As a subset of question answering systems, dialogue systems target to interact with human users through a dialog expressed in natural language. As a subset of dialogue systems, chatbots try to simulate human-like conversations. The paper provides an overview of the typical aspects of the studied search services, including process models, data preparation and presentation, common methodologies and categories.
... Most of the standard request parts are uncommonly notable, yet their results are sometimes mistaken that have a lower precision and high audit. They have to find the ramifications of terms and enunciations used in pages and their associations [5][6] [7]. Canny and Current inquiry structures, as SWSE, Swoogle, Falcons Object Search are arranged reliant on the semantic method to manage vanquish the standard issues. ...
Ranking for multilingual data recuperation is a movement to rank files of different languages solely subject to their essentialness to the inquiry paying little brain to request's language. The main goal of a data retrieval process is to supply the data which is queried by the client. Sometimes the data that is requested by the client will not be available in the client's understandable language. While there are some times where the client will utilize the data in the language which is not understandable by the client which results in issues to resolve the queries posed by them. The essential objective behind Multilingual Information Retrieval is to find the relevant information available paying little heed to the language used in the request. We presented the web page ranking algorithm with illustrative circumstances by interfacing different pages. The results are dismembered by simulating the page algorithm using built simulating system.
... Once a different keyword is found, they expand on it to find similar keywords for that keyword [17]. Keyword suggestion tools usually aid the process of finding similar keywords such as in [18] where substitutional keywords are the suggestions for the query. There are many techniques used in keyword search engines such as identify the core of the keyword, research related search terms, create a list of main terms and long-tail keywords, use the Google AdWords keyword planner…etc. ...
... There are many examples of SSEs such as Hakia, DuckDuckGo, Swoogle… etc. The methods to store information within the SW technology are able to answer complex queries given to a search engine [18] [13]. ...
... It is representing the primary layer used in SW. RDF is very important to represent data which can be processed by machines [18]. The method that is used to identify and provide the relationship among the resources called graph model. ...
... The ontology [1] works on the science of meaning so as to produce relevant results. The major limitation of the traditional search engine lies in their inability to understand the meaning of the keywords and expressions used by the user in the search query which may be due to the words having same meanings or the words having several meanings (polysemy semantics search engine tries to make logic or sense of search results based on its context and is able to detect the concepts which structure the texts [2]. For instance, if you search for "elections" a semantic search engine might retrieve the resulting documents that contain the words "vote", "campaign" and "ballot", even if the word "elections" is not there in the source document. ...
Information Retrieval has become the buzzword in the today’s era of advanced computing. The tremendous amount of information is available over the Internet in the form of documents which can either be structured or unstructured. It is really difficult to retrieve relevant information from such large pool. The traditional search engines based on keyword search are unable to give the desired relevant results as they search the web on the basis of the keywords present in the query fired. On contrary the ontology based semantic search engines provide relevant and quick results to the user as the information stored in the semantic web is more meaningful. The paper gives the comparative study of the ontology based search engines with those which are keyword based. Few of both types have been taken and same queries are run on each one of them to analyze the results to compare the precision of the results provided by them by classifying the results as relevant or non-relevant.
... They lack to find the meanings of terms and expressions used in web pages and their relationships. The problem lies in the existence of words that have many meanings in natural languages [7]- [9]. ...
... It is divided into four main components: data discovery, the creation of metadata, data analysis and retrieval [10]. The most significant drawback of this system is that it is not a generalpurpose search system and is limited to predefined ontologies files [7]. Also, it has some weaknesses such as weak indexing of massively large data and time-consuming of query response as discussed in section 5. ...
... Hakia [7] is another system that acts as a comprehensive semantic engine that works for general purposes. It is called a search engine based on meaning rather than search terms [7]. ...
Today, most users need search engines to facilitate search and information retrieval processes. Unfortunately, traditional search engines have a significant challenge that they should retrieve high-precision results for a specific unclear query at a minimum response time. Also, a traditional search engine cannot expand a small, ambiguous query based on the meaning of each keyword and their semantic relationship. Therefore, this paper proposes a comprehensive search engine framework that combines the benefits of both a keyword-based and a semantic ontology-based search engine. The main contributions of this work are developing an algorithm for ranking results based on fuzzy membership value and a mathematical model of exploring a semantic relationship between different keywords. In the conducting experiments, eight different test cases were implemented to evaluate the proposed system. Executed test cases have achieved a precision rate of 97% with appropriate response time compared to the relevant systems.
... Semantic search engines likes woogle, falcon, SWSE have structured data that handles data in OWL or RDF format only. Moreover, XML takes in accord the Syntactic level but not the reasoning [2]. Employing SWSE(Semantic Web Search Engine) for Searching and Browsing Linked Data: [3]. ...
... Dalji tehnološki napredak dovešće i do daljeg razvoja upravljanja znanjem. Već su aktuelna razmatranja efekata primene semantičkog koncepta Web 3.0 (Jain et al, 2015) u upravljanju znanjem (Ahuja & Kumar, 2017;Dascalu et al, 2017). Web 3.0 nastao je integracijom Web 2.0, semantičkog weba i povezanih podataka (Hendler, 2009). ...
The purpose of the thesis is to identify the occurence and nature of the interconnection between the application of organizational knowledge preservation and upgrade concepts and efficiency of the stakeholder communications of the companies. The main research topics are practices and attitudes of the companies from the Western Balkans and the Middle East related to the management of the organizational knowledge and its usage for shaping and implementation of the stakeholder communications activities. The thesis incorporates a detailed analysis of the existing information and achievements in the areas of organizational knowledge, knowledge management and stakeholder communications, as well as identification of challenges and opportunities. This aspect is covered with a detailed overview of scientific and expert literature from these areas until 2017. The data related to practices and attitudes of the companies are collected through structured interviews with 32 companies – 16 from the Western Balkans and 16 from the Middle East.
Based on the literature review and findings from the present study, interdependence between the existence of organizational knowledge preservation and upgrade system and the success of the stakeholder communications has been determined. The hypothesis: »Existence of the comprehensive organizational knowledge preservation and upgrade system enhances capacities of an organization for successful stakeholder communications« is directly supported through the research findings: 87,50% of the respondents consider the existence of the comprehensive organizational knowledge preservation system as the enhancing factor for capacities of an organization for successful stakeholder communication. The absolute majority of the respondents considers companies who systematically keep and upgrade the organizational knowledge to be more successful in communication than the ones who do not do it and this finding directly supports identically formulated sub-hypothesis.
The results of the research support the sub-hypothesis stating that companies from the Western Balkans apply organizational knowledge in the stakeholder communications in a different way compared to companies from the Middle East. Numerous differences related to preservation, upgrade and application of the organizational knowledge are recognized between the companies from the above mentioned regions. Based on the findings from the study and literature review, possible directions of development of the scientific research in this area are identified. Also, measures for fostering organizational knowledge preservation and usage, as well as for increasing efficiency of the stakeholder communications, are proposed.
... In [10] the authors-Ranjna Jain, Neelam Duhan, A.K Sharma, have explained the importance of search engines. Also with a lot of improvements in searching technique, yet the search engine displays the result based on keywords and does not understand the meaning of the keywords. ...
