Web-based knowledge systems

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Extracting knowledge from web communities and linked data for case-based reasoning systems

Extracting knowledge from web communities and linked data for case-based reasoning systems

Web communities and the Web 2.0 provide a huge amount of experiences and there has been a growing availability of Linked (Open) Data. Making experiences and data available as knowledge to be used in case-based reasoning (CBR) systems is a current research e ff ort. The process of extracting such knowledge from the diverse data types used in web communities, to transform data obtained from Linked Data sources, and then formalising it for CBR, is not an easy task. In this paper we present a prototype, the Knowledge Extraction Workbench (KEWo), which supports the knowledge engineer in this task. We integrated the KEWo into the open-source case-based reasoning tool myCBR Workbench. We provide details on the abilities of the KEWo to extract vocabularies from Linked Data sources and generate taxonomies from Linked Data as well as from web community data in the form of semi structured texts.
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Extending the UTAUT to measure the adoption of web based knowledge sharing systems in Saudi universities

Extending the UTAUT to measure the adoption of web based knowledge sharing systems in Saudi universities

Jolaee et al. (2014) suggested that knowledge sharing is crucial activity in knowledge-based organizations, like universities, since the majority of the academics are knowledge workers who engage in teaching and research activities. Their view is supported by Seonghee and Boryung (2008) who stated that faculty members share the same common missions where academics work as the disseminators of knowledge through teaching and as the producers of knowledge through conducting research. Fullwood, Rowley and Delbridge (2013) found that knowledge sharing depends on individual behaviour toward accepting or rejecting the use of web technology for disseminating knowledge. Behavioural intention is an indicator of an individual’s readiness to share knowledge and can be affected negatively or positively by various factors (Alammari and Chandran, 2017). In this research, behavioural intention refers to the academic’s likelihood to share knowledge using web technology.
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Dynamic Web Content Filtering Based on User's Knowledge

Dynamic Web Content Filtering Based on User's Knowledge

of the Web document, to filter out unneeded information, the latter uses other users’ judgment against the contents, such as a rating scale. In the commercial area, URL filtering and IP systems are extensively used to eliminate irrelevant information because they are very easy to implement, work very fast, and produce acceptable success rates. However, the performance of this kind of system entirely depends on the exactness of registered URLs and IPs. If the filtering systems have incomplete blocking URLs and IPs list, the efficiency of the filtering system is quickly degraded. Nevertheless, it is very difficult to keep up with all relevant URLs and IPs because the Web is continually changing with no notification. The filtering systems will deteriorate without appropriate acquisition of new filtering knowledge. The content based filtering system and the collaboration based filtering system can be employed to enhance URL and IP based filtering systems.
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Knowledge based systems text analysis

Knowledge based systems text analysis

Some entity linking systems try to leverage the whole Web information to identify candidate entities via Web search engines (such as Google). Specifically, Han and Zhao [61] submitted the entity mention together with its short context to the Google API and obtained only Web pages within Wikipedia to regard them as candidate entities. Dredges et al. [83] queried the Google search engine using the entity mention and identified candidate entities whose Wikipedia pages appear in the top 20 Google search results for the query. Lehmann et al. [69] and Monahan et al. [73] stated that the Google search engine is very effective at identifying some of the very difficult mappings between surface forms and entities. They performed the query using the Google API limited to the English Wikipedia site and filtered results whose Wikipedia titles are not significantly Dice or acronym based similar to the query. Lastly, they utilized the top three results as candidate entities.
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Toward a new model for the adoption of web based knowledge sharing systems amongst academics in Saudi Arabian higher education institutions

Toward a new model for the adoption of web based knowledge sharing systems amongst academics in Saudi Arabian higher education institutions

This research considers the application of knowledge sharing in Saudi Arabian universities. Most Saudi universities are not geographically co-located as they have dispersed campuses in rural and urban areas. Therefore, expert academics need to travel between these campuses to share knowledge with others who have common interests. Additionally, many years of teaching experience could be lost due to academic retirement without being recorded in a proper knowledge sharing system. Consequently, face-to-face communication is no longer an effective way of sharing knowledge and it would be more valuable if the knowledge were documented and shared in a way that encourages novice teachers to use them [1]. Thus, universities need to implement a knowledge sharing system that could facilitate the flow of knowledge amongst academics and could overcome the challenges mentioned above. In order to ensure that a knowledge sharing system can be well implemented and used in the academic context, there is a need to investigate technology acceptance among academics [10]. Previous studies have investigated user acceptance of using new information systems, however, to the best of the researchers’ knowledge, there is a lack of studies that investigate academics’ perspective on using web-based knowledge sharing systems in Saudi Arabia [11]. Thus, this study explores that factors that influence academics’ behaviour towards using web-based knowledge sharing systems in Saudi Arabian higher education institutions.
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Knowledge based systems text analysis

Knowledge based systems text analysis

denominated entity mentions appearing in Web text with their corresponding entities in a knowledgebase, which is called entity linking. Entity linking can facilitate many different tasks such as cognizance base population, question answering, and information integration. As the world evolves, incipient facts are engendered and digitally expressed on the Web. Consequently, enriching subsisting cognizance bases utilizing incipient facts becomes increasingly consequential. However, inserting incipiently extracted cognizance derived from the information extraction system into a subsisting cognizance base ineluctably needs a system to map an entity mention associated with the extracted erudition to the corresponding entity in the cognizance base. For example, cognation extraction is the process of discovering utilizable relationships between entities mentioned in text and the extracted cognation requires the process of mapping entities associated with the cognation to the erudition base afore it could be populated into the cognizance base. Furthermore, an immensely colossal number of question answering systems rely on their fortified cognizance bases to give the answer to the user’s question. To answer the question “What is the birth date of the famous basketball player
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Knowledge Based Systems Text Analysis

Knowledge Based Systems Text Analysis

Tidally and the Web has become one of the most sizably voluminous HE amount of Web data has incremented exponent data repositories in the world in recent years. Plenty of data on the Web is in the form of natural language. However, natural language is highly equivocal, especially with reverence to the frequent occurrences of denominated entities. A denominated entity may have multiple names and a designation could denote several different denominated entities. On the other hand, the advent of cognizance sharing communities such as Wikipedia and the development of information extraction techniques have facilitated the automated construction of astronomically immense scale machine-readable cognizance bases. Cognizance bases contain affluent information about the world’s entities, their semantic classes, and their mutual relationships. Such kind of eminent examples include DBpedia YAGO Freebase Ken tall Read the Web and Probes. Bridging Web data with cognizance bases is propitious for annotating the plethora of raw and often noisy data on the Web and contributes to the vision of Semantic Web. A critical step to achieve these goalies to link denominated entity mentions appearing in Web text with their corresponding entities in a knowledgebase, which is called entity linking. Entity linking can facilitate many different tasks such as
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wEBMT: Developing and Validating an Example Based Machine Translation System using the World Wide Web

wEBMT: Developing and Validating an Example Based Machine Translation System using the World Wide Web

Note that none of these aligned resources would be possible in a TM system. The problem of segmentation is not an inconsiderable one in all EBMT systems, but we (and others) have found that using the marker hypothesis can greatly facilitate such a process. We shall show in subsequent sections that because such knowledge sources are derived automatically from the original translations obtained via Web-based MT systems, the translations obtained in our EBMT process are largely of high quality, are ranked highly in the set of output translation candidates, and may be generated in almost all cases—all this despite the fact that the original translations obtained via the Web contain many errors, and that the source phrases to be translated were selected from a mere fraction of the rule types in the Penn-II Treebank.
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An Introduction to Web-based Support Systems

An Introduction to Web-based Support Systems

The profile, resource, and data management components form a solid basis of WRSS. A research support system consists of many sub-systems to support different activities. They share common data and knowledge bases. We list some specific supporting functionality: exploring support, retrieval support, reading support, analyzing support, and writing support. As a specific type of WSS, the WRSS assist scientists to improve their research quality and productivity. The feasibility of such systems is based on the assumption that relatively systematic approach exists in scientific research. Furthermore, a general research process can be established, consisting of several steps or phases, such as idea generation, exploration, problem definition, procedure design and planning, observation and experimentation, data analysis, results interpretation, and communication. A number of activities are involved in each of these phases.
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Ontology Based Knowledge Grid in Semantic Web to Discover Knowledge in Distributed Environment

Ontology Based Knowledge Grid in Semantic Web to Discover Knowledge in Distributed Environment

the processes involved in the developing, deploying and utilizing E-course for deployment in the State of Kerala in India. It made possible by advanced technology web-servers based on a new architecture to establish effective and well managed learning management and collaboration systems and subject-specific interface which support to enhance the quality of education in distributed environment. The Knowledge Gr id based knowledge discovery model is builds on a computational grid which provides dependable and consistent access to computational resources. It used basic grid services and defines a collection of extra additional layers to develop the services of distributed knowledge discovery on the distributed connected resources where each node can be a sequential or a parallel machine. The Knowledge Grid enables the collaboration of scientists that must mine data that are stored in different research centers as well as executive managers that must use a knowledge management system that operates on several data warehouses located in the different company establishments. This represented an initial step for the design and implementation of a grid architecture that integrate different data mining techniques, algorithm and computational grid resources in the distributed environment 7 . The Grid-based data mining and
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Knowledge based Recommendation System in Semantic Web   A Survey

Knowledge based Recommendation System in Semantic Web A Survey

Non-Monotonic is the reverse of Monotonic where adding of new information can affect truth value of existing information. Defeasible reasoning and Answer set programs are examples of non-monotonic reasoning systems. Defeasible reasoning is a rule-based approach which works with incomplete and inconsistent information [25]. It can represent facts, rules, and priorities among rules. Answer Set Programs are non-monotonic logic programs based on the Answer Set Semantics, which use extended logic programs for reasoning and problem solving by considering possible alternative scenarios [26]. Evolution updates and events represent dynamic aspects of personalization in Semantic Web [27]. This approach represents reactive behavior specifying actions to be taken according to the situation by writing rules. Event- Condition-Action paradigm is used to represent the reactive behavior. An occurrence of a specific activity is an event, when an event occurs, a condition is checked; if condition is satisfied, an action is carried out.
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Developing an Integrated Computational Environment for the Detailed Design of a Mixing Impeller

Developing an Integrated Computational Environment for the Detailed Design of a Mixing Impeller

Research into engineering workflows has primarily focused on processes that utilize mass production manufacturing technologies. These frameworks are often divided into the conceptual, preliminary, and detailed phases. Two areas of particular interest within engineering design that impact workflow are (1) developing tools that address the management, organization, communication, and remembrance of information during the design process; and (2) developing tools that reduce the computational time while increasing the range of options explored during the design process. In many ways these two issues interrelated. As high fidelity modeling tools are adapted to address conceptual and preliminary design, analysts will be able to create large amounts of data that may or may not provide meaningful guidance. Several researchers have recently developed software tools for the management and organization of the information produced during the design process. These knowledge management systems try to capture information as the design progresses and enable designers, engineers, and other collaborators to view the same information. For example web based knowledge management systems have been proposed as a means to overcome the disparity in engineering design knowledge due to physical distance and differing skills and roles between actors while using multidisciplinary optimization. 16 Automation of the identification of design
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Technique for Detecting Zero Day Attack by using Signature based and Knowledge Based Method

Technique for Detecting Zero Day Attack by using Signature based and Knowledge Based Method

Web service firewalls, have been introduced to protect services. However, attackers can still compromise web services and do their malicious actions. Intrusion detection systems (IDS) are appropriate for defence in depth; and sit behind of firewalls in the security structure of an enterprise. However, network IDSs fail to detect attacks in Web service layer. In this paper, we propose an intrusion detection system for web services (WS-IDS), to detect malicious behaviors of the requesters of a typical web service. This idea is motivated by considering the inability of the existing IDSs to detect the attacks in web service layer. WS- IDS can be used in addition to other security
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Domain Knowledge Engineering Based on Encyclopedias and the Web Text

Domain Knowledge Engineering Based on Encyclopedias and the Web Text

Artificial methods are usually used in constructing the common sense knowledge base, such as CYC[1], WordNet[2], EuroWordNet[3], HowNet[4], and CCD[5] etc. That’s because common sense is steady comparatively and it can not be affected by the task, also it can be reused by various kinds of system when constructed. For instance, since the WordNet was established in 1985, it had been widely used in IR, Text categorization, QA system etc. Similarly, the HowNet is being used in many Chinese information procession systems. It’s worthy of large-scale devotion for long-time using.
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Improved compatibility with knowledge sharing in cloud Environment

Improved compatibility with knowledge sharing in cloud Environment

Abstract: Developments in computing are influencing several aspects of education. the aim of this paper is to assess the potential price of cloud computing as a platform for knowledge sharing. Specially, the paper can discuss however cloud computing is totally different from alternative forms of computing and what makes it distinctive. Similarly is that this, the potential blessings and drawbacks of mistreatment cloud computing as a platform for knowledge sharing is going to be printed. Finally, the necessities of implementing cloud computing are going to be mentioned, at the side of associate assessment of the challenges to implementation, and a few potential ways that to beat them. Providing knowledge sharing services employing a cloud-based platform will scale back prices, will be easier to take care of and update, and supply advantages to end users in terms of security and compatibility. However, cloud-based learning systems need quick and reliable web access, and problems close the safety of a cloud stay unclear.
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RAPID DEVELOPMENT OF KNOWLEDGE-BASED CONVERSATIONAL RECOMMENDER APPLICATIONS WITH ADVISOR SUITE a

RAPID DEVELOPMENT OF KNOWLEDGE-BASED CONVERSATIONAL RECOMMENDER APPLICATIONS WITH ADVISOR SUITE a

expectations and base the product proposal on this estimate. From the perspective of the user interaction style, a system that also understands natural language utterances appears to be promising at a first glance. In the A DVISOR S UITE system, however, we decided to follow a form-based, system- driven approach and did not rely on natural language interaction for different reasons. First, in a natural language system, we do not only have to develop knowledge bases for the recommendation domain but also have to build a large repository of phrases needed for casual conversation which one typically expects from such a system to be capable of d . More importantly, we claim that in particular users with little background knowledge in the domain may have their problems in keeping the conversation running, as they might not even know which questions to ask or which terms to use. In addition, we argue that online users are well-acquainted with fill-out forms and navigation features in standard Web pages and will thus feel more comfortable and being in control when using the system. Finally, when using natural language systems, there is some risk that end users attribute more intelligence to the system than is warranted and disappointedly quit using the system that for instance does not understand certain utterances.
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ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS: KNOWLEDGE-BASED SYSTEMS

ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS: KNOWLEDGE-BASED SYSTEMS

The Web is allowing us to deploy ES directly on it, to provide expertise to users by running directly on the Web. For example, Exsys WREN is a Web Runtime Engine for Exsys (try it out). Help desk software, essentially ES, are running on the Web pages of many technical support groups. Ginesys Corp. has such software as a part of its K-Vision ES shell. Furthermore, anytime expertise is required for customer support (e.g., in advertising to help a customer choose a product to order or use), it can be provided over the Web by an ES.

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Developing a web-based SKOS editor

Developing a web-based SKOS editor

The Simple Knowledge Organization System (SKOS) standard was introduced to the wider community by a 2005 World Wide Web Consortium (W3C) working draft [1], and further developed and refined in a 2009 W3C rec- ommendation [2, 3] 1 . Since then, SKOS has become the de facto standard for representing thesauri, lexicons, vocab- ularies, taxonomies, and classification schemes, both as a useful data format in its own right, and as a means for sharing resources on the semantic web. In this paper, we describe the development of a web-based, free, open- source SKOS editor suitable for the creation and curation of knowledge organization systems in general, and health- related lexicons designed to support clinical Natural Language Processing (NLP) in particular.
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Smart Tutor an Intelligent Tutoring System for C Sharp Programming

Smart Tutor an Intelligent Tutoring System for C Sharp Programming

Firstly Currently most web based learning systems are simple websites that give only the text based lecture or videos, other than that if a user appear to have no knowledge about the concept won’ t know what should learn first or after, the proposed system is an approach to provide complete knowledge about C# programming to a person not even familiar with programming using proper sequence, which is the most important aspect a teacher make effort to provide knowledge over the semester to the class, the sequence the system uses is generated through people related to teaching in university. Secondly most web based learning system didn’t create suggestion on the basis of previous record of user as they didn’t save any. The proposed system is functioned to create suggestion on the basis of logs created every time user learned a concept and system make an acknowledgement for user and get info about user knowledge about the given concept and create a log for it, so next time user login will proceed to next step on the other hand these acknowledgement are useful for system to create learning sequence, suggestions and alerts to user for prerequisites. This system is also designed to take quiz for any concept if user acknowledges about the quiz that is one of the acknowledgment system ask from users. These quiz result are useful for system as to decide the probability of user knowledge gained over the concept for suggestion to go further from the sequence or review the previous one. The proposed system can be used with any other language but with only the concept defined on the network.
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Animal Knowledge based Systems in Egypt

Animal Knowledge based Systems in Egypt

Improved animal productivity is one of the main objectives for veterinary services in developing countries to insure the food sustainable. Using information and communication technology to develop systems that assist animals’ breeders will contribute in this objective. Knowledge based system have the ability to transfer knowledge from veterinarian experts and animal production experts to both young veterinarians and animals breeders. Knowledge based systems also known as expert systems which arose as a branch of applied artificial intelligence and were developed by the AI community in the mind-1960s [1]. Knowledge based system is a computer program which includes the knowledge and analytical skills of one or more human experts in a particular problem domain [2]. The idea of knowledge based system construction is to code knowledge into a computer program so that can be consulted in much the same way that one consults a human expert. Well-designed knowledge base systems imitate the reasoning process of human experts to solve specific problems and can be used by non-experts to improve their problem-solving capabilities and by experts as knowledgeable assistants [3].
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