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a rule based system is a special type of expert system which consists of a set of rules. In practice, rule based systems can be built by using expert knowledge or learning from real data. Due to the vast and increasing size of data, the latter approach has become quite popular for building rule based systems. In particular, rule based systems can be built through use of rule learning algorithms, which...
Acquisition of high quality structured knowledge that is immediately useful for reasoning algorithms has been a longstanding goal of the Artificial Intelligence research community. With the recent advances in crowdsourcing, the sheer number of internet users and the commercial availability of supporting platforms have come a new set of tools to tackle this problem. Although numerous systems and methods...
Stories have become an important element of games, since they can increase their immersion level by giving the players the context and the motivation to play. However, despite the interactive nature of games, their stories usually do not develop considering every decision and/or action the players are capable of, because depending on the game size, it would take too much effort to author alternative...
Context-driven query extraction for content-basedrecommender systems faces the challenge of dealing with queriesof multiple topics. In contrast to manually entered queries, forautomatically generated queries this is a more frequent problem. For instances if the information need is inferred indirectly viathe user's current context. Especially for federated search systemswere connected knowledge sources...
Of all the perspectives about what inconsistencies entail and how we can handle them, one that escapes our attention is that inconsistencies can serve as effective stimuli to learning because they often help reveal the inadequacies, gaps, deficiencies, or boundary conditions in an agent's problem-solving knowledge. In this paper, we describe a new machine learning approach: inconsistency-induced learning...
Machine Translation (MT) has progressively evolved since 1940's. It is a topic of active research now a days as the results found so far from machine translation tools are very unrealistic as compared to the human translation. Many different new approaches and techniques have evolved along with the new advent in machine translation. There are different paradigm of machine translation including Statistics...
CrossCult (www.crosscult.eu) is a 3-year H2020 research project, which started in March 2016. It involves 11 European institutions and 14 associated partners from the areas of Computer Science, History and Cultural Heritage. The goal is to spur a change in the way European citizens appraise History, fostering the re-interpretation of what they may have learnt in the light of cross-border interconnections...
Entity relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel Web-mining-based Chinese entity relation extraction approach. This approach explicitly defines and explores the Web mining process and relation feature words for entity relation extraction. The results of the research indicate this method is promising.
Case-Based Reasoning (CBR) interests the scientific community, whom are concerned with scalability in knowledge representation and processing. CBR systems scale far better than rule-based systems. Rule-based systems are limited by the need to know the rules of engagement, which is practically unobtainable. The work presented in this paper pertains to knowledge generalization based on randomization...
In this paper we propose a Fuzzy Cognitive Maps (FCMs) to recommender Learning Resources in a Smart Classroom. We have proposed a Smart Environment for a Classroom in previous works, based on Multi-agent Systems, called SaCI. One of its agents is a recommender system of Learning Resources. In this paper, we define this recommender system using Fuzzy Cognitive Maps. Our recommender system exploits...
Adapting application to diverse/dynamic domains is required to enlarge pervasive computing use, to satisfy people demand in terms of continuity of services. In addition, the proliferation of smart devices, ubiquitous services motivate the need for a quick development of applications that support people in dynamic domains. Inappropriately, this quick development is often associated a discard of domain...
This paper proposes an alternative scheme to detect design patterns in the early design stage. Both structural and behavioral designs primarily drawn in class diagram and its associated sequence diagrams are considered. Our detection approach exploits the knowledge base defined in ontology and the relevant inference rules to detect the design patterns. The Similar structural design patterns are effectively...
Entity linking (EL) is the task of mapping name mentions in web text to their entities in a knowledge base. Most of earlier EL work in the knowledge based approach is usually formulated as a ranking problem, either by (i) non-collective approaches with supervised models, or (ii) collective approaches by leveraging global topical coherence which means semantic relations between entities through graph-based...
Warnings can help prevent damage and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks, or issue early-warnings. In a socially and environmentally responsible word, we need effective Early-Warning Systems (EWS). EWS are...
Urban search and rescue (USAR) missions can benefit a great deal from teams of mobile robots endowed with advanced perception capabilities. To effectively collaborate with humans, these robots should have situation awareness about their robotic and human teammates, for intuitive decision making. Moreover, robots should be able to contextually share information so that humans can benefit from augmented...
Word Sense Disambiguation (WSD) is the task of automatically choosing the correct meaning of a word in a context. Due to the importance of this task, it is considered as one of the most important and challenging problems in the field of computational linguistics and plays a crucial role in various natural language processing (NLP) applications. In this paper, we present an improved version of a recent...
In Natural Language Processing, Word Sense Disambiguation is defined as the task to assign a suitable sense of words in a certain context. Word Sense Disambiguation takes an important role and considered as the core research problem in computational linguistics. In this research, we conduct an experiment with Adapted Lesk Algorithm compared to original Lesk Algorithm to improve the performance of...
Collaborative design entails sharing knowledge in an effective way and from a variety of sources, which raises the need of developing technology-enabled systems that can improve decision making by streamlining complex analysis and synthesis processes and facilitating communication and negotiation in the design process. While previous research predominantly focuses on a particular aspect of design...
Information Present in Different language and Structure gives Rise to language as barrier in information retrieval. Informative Document on queen Elizabeth is been writing by foreign language English which makes its difficult for a Marathi reader to understand and seek History of England, on Similar lines Literature Work on Shivaji is mostly documented in Marathi which makes foreign Historians difficult...
With the rapid development of Internet, how to extract personal relations from Internet has become an important research topic in information extraction. However, current relation extraction researches mainly focus on the processing of English language, the researches focus on Chinese are less. At the same time, there are two main problems in current personal relation extraction approaches: 1) it...
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