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Dealing with user incidents, questions and problems are important tasks during the maintenance of the software. It is specially important for service providers, which must provide the users with a quick and reliable answer. Many times the incident has been previously solved for other users. In these cases, an appropriate knowledge management strategy could help to improve response times as well as...
Data availability in online social networks as well as the business world has lately not been an issue. Vast amounts of data are being generated by social networking users in the form of informal interactions. What has been an issue, is the transformation of data into useful information, that in time and with appropriate processing becomes knowledge. In this paper we examine knowledge generation under...
An extension of the HTN-DL web service model is presented, including rules for web service behavior and compliance validation against customer requests. The intention is to overcome the limitations of HTN-DL and OWL-S in covering business constraints in service selection and also the limitation of preconditions. The proposed approach validates a web service obtained through HTN-DL planning, for compliance...
In this paper, we address the problem of how toexploit folksonomy systems and social bookmarking tools toenrich DBpedia ontology while unifying the formal knowledgerepresented by DBpedia ontology with the informal knowledge emerging from tagging. Our approach taps into external tools such as the sense inventory WordNet to correct mistakes resulted from the free tagging and takes advantage from semantic...
The aim of this paper is to illustrate a technique of integration between Tutor Bot and QR codes, used to label real objects during learning activities in direct educational contexts (egc. Situated learning and Authentic Learning). Tutor Bot knowledge base, structured in AIML (Artificial Intelligent Markup Language), is questioned in natural language using a mobile device (smart-phones, tablet, etc...
In this paper, an intelligent concept based search engine has been presented that can be used as a multilingual platform for different search queries. It retrieves those results pages also which don't have directly the keywords but contains the synonyms or related words. In response to a query for the word “car” it will also retrieve web pages which don't have directly the word “car” but have the...
In this paper we analyze the principal preconditions and limitations for designing a competence-based Recommender System. In detail this analysis is contextualized in the ARISTOTELE European project. In the second part of the paper an architectural view is proposed taking in consideration the objective to propose standard and non-standard suggestions. This solution will permit to insert serendipity...
The formalization and manipulation of complex and not yet assessed rules by clinicians are critical for Decision Support Systems (DSSs) performance in supporting remote monitoring of chronic patients. Sometimes, structural anomalies, such as inconsistency and redundancy, can occur. This work presents a novel system, named Consistency Checker, aimed at verifying the reliability of condition-action...
A system for computer-aided guided interactive diagnosis is presented. It is based on dynamic taxonomies, a knowledge management model that allows the guided interactive exploration of complex information bases. Clinical diagnosis is performed by exploring and thinning out candidate pathologies on the basis of clinical signs and other observable features in a guided yet practitioner-centered way....
Multi-language data impairs the application of mining techniques in a generalized form, since language remains an impenetrable barrier. The advances on domain driven data mining and the study of its semantic aspects open a first window over it, in particular the D2PM framework [1]. This paper proposes a new method for mining patterns over multi-language data, through the use of the D2FP-Growth algorithm...
Robots need to have knowledge of their environment to be able to successfully complete service tasks. Most knowledge inference mechanisms assume complete and correct knowledge about the environment. Real world environments are often uncertain and only partially observable. Thus, intelligent service robots may have an incomplete knowledge base which includes true positives as well as false negatives...
The data required for automatic optimization of user services usually exists in current systems, but that data is not modelled or linked in a way that facilitates automation. Knowledge engineering is a promising approach for managing the disparate communication service quality management information data sets and the links across those data sets. Once a knowledge base is in place, semantic techniques...
Motivated by the increasing importance of knowing which operating systems are running in a given network, we evaluated operating system discovery (OSD) tools. The results indicated a serious lack of accuracy in current OSD tools. This thesis proposes a new approach to OS discovery which addresses the limitations of existing tools and leads to a more flexible, less intrusive, and much more accurate...
Decision making whenever and wherever it is happened is key to organizations success. In order to make correct decision, individuals, teams and organizations need both knowledge management (to manage content) and collaboration (to manage group processes) to make that more effective and efficient. In this paper, we explain the knowledge management and collaboration convergence. Then, we propose a formal...
Multi-modal sensor fusion recently became a widespread technique to provide pervasive services with context-recognition capabilities. However, classifiers commonly used to implement this technique are still far from being perfect. Thus, fusion algorithms able to deal with significant inaccuracies are required. In this paper we present preliminary results obtained with a novel approach that combines...
Manual knowledge acquisition is extremely laborious and time consuming. In this paper, we propose a new automatic method for domain knowledge acquisition by semantic annotating and pattern mining. This method makes use of Minipar to label sentences and extract structural patterns. Semantic bank is proposed to annotate and represent concepts with semantic labels considering sentence context. The method...
Semantic web using personalization support to provide relevant search results for searcher. Ontology is an effective method for modelling digital collections and user contexts. User profiling is commonly employed nowadays to enhance usability as well as to support personalization, adaptivity and other user-centric features. This work aims at creating a user profile ontology that incorporates concepts...
Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge represented logically (i.e., knowledge base). But, the ordinary users don't know well the complex formal query language and schema of the knowledge base. So, the system should interpret the meaning of user's keywords. Such requirements are conspicuous especially in smart media...
In this paper we present a new approach to belief revision. In contrast to traditional formalizations of this problem, where all pieces of information included in a knowledge base have identical status, we explicitly distinguish between observations, i.e., facts which an agent observes or is being told, and facts representing a general, sometimes defeasible, knowledge about the considered world.1...
Within the paper we discuss the issue of designing well-founded contextual knowledge bases. Following the base idea that contextualization is a vital part of conceptualization, we extend the definitions of selected notions of OntoClean, the well-known method of assessment of taxonomies, towards contextual approach. This allows us to formulate a set of desirable qualities for context-semantic knowledge...
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