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Recommendation technique is a personalized search used to assist a user access information/services that are related to his preferences and interests, or to the preferences and interests of similar users. The main challenge of personalized Information Retrieval is the modeling and the integration of user profiles. In this paper, we propose a generic model of user profiles based on the search history...
In this paper, we present a generic model to enrich user profiles by means of contextual and temporal information. This reflecting the current interests of these users in every period of time defined by a search session, and infers data freshness. We argue that the annotation of resources gives more transparency on users' needs. Based on this idea, we integrate social tagging in order to exploit part...
Information overload is one of the most important problems in context of personalized document retrieval systems. In this paper we propose to use ontology-based user profile. Ontological structures are appropriate to represent relations between concepts in user profile. We present a method for determining user profile based on his current activities. Results obtained in experimental evaluation are...
Many household appliances draw standby power, which can be reduced to save total energy consumption of a household. Smart plugs are proposed for effectively reducing standby power of an appliance by monitoring and cutting power when the appliance is no longer in use. However, the level of intelligence it leverages is minimal such that it still requires a direct manipulation by the user and does not...
This paper presents a method to validate the insertion of a new concept in an ontology. This method is based on our previous works which add new concepts in a basic ontology using a general ontology (genaral ontology contains all the concepts of the basic ontology). To verify the semantic relevance of an ontology, we have proposed a method with three steps. First, we have found the neighborhood of...
This paper describes performance of an interpreter uncovering meanings of prepositions in "master" — preposition — "slave" constructions. The basis of the semantic interpreter is a set of "if A, than B" rules, with the left parts containing lexical and semantic markers of the "masters" and the "slaves" and morphological markers of the "slaves"...
In this paper, we represent the context based weighting scheme for vector space model to evaluate the relation between concept and context in Information storage and retrieval system. A meaning of a word is relatively decided by a context dynamically. A vector space model, generally use a static weighting scheme for term document matrix like latent semantic indexing (LSI), co-occurrence or correlations...
In this paper, we represent a dynamic context-dependent weighting method for vector space model. A meaning is relatively decided by a context dynamically. A vector space model, including latent semantic indexing (LSI), etc. relatively measures correlations of each target thing that represents in each vector. However, the vectors of each target thing in almost method of the vector space models are...
Data evolution is the process of semantics change for data product, in which data product has intrinsic semantics as well as extension semantics. This paper presents an ontology framework for evolution of plain text. The semantics of plain text is modeled as DATAGENOME ontology, including CONNOTATION ontology for expressing the intrinsic semantics and CONTEXT ontology for representing the extension...
With the fast growing development of the Web, the adoption of ontologies to improve the exploitation of information resources, is already heralded as a promising model of representation. However, the relevance of information that they contain requires regular updating, and specifically, the addition of new knowledge. Recently, new research approaches were defined in order to automatically enrich ontology...
Service discovery is the premise of service composition. The existing service discovery methods only consider individual service functions and static properties, less considering the inherent dependencies between the composite services. The data dependencies between services reveal the logic correlation between the composite services, but it is of great significance for the service composition and...
The considerable improvement in the biotechnogical field and the adoption of screen techniques such as high throughput arrays produced a spread of biological and genetical data and scientific papers, mostly diffused on the Web. Even if the huge amount of available information represents a major step forward for the biomedical research field, the main effort for a scientist is to evaluate the correlation...
In this paper, we proposed a novel recommendation model based the synergistic use of knowledge from repository which includes users behavior and items property. This model defined user profile and item profile, and constructed the candidate recommendation set by using Formal Concept Analysis and extended inference. We attempted to apply FCA mapping the relationship between user's preference and item...
A common challenge for applications requiring information and knowledge fusion is the conversion of data streams into knowledge adapted to the context of usage. In the context of the project Integrated Mobile Security Kit, this paper focuses on the knowledge fusion sub-system. It integrates different fusion aspects based on a common domain model and embedded into a distributed and mobile infrastructure...
Aiming at the problem of the "semantic gap" and the "dimensionality curse", this paper discussed the model of cross-media retrieval. The methods of feature extraction and fusion of multimedia were given for processing high-dimensional data, and a nonlinear hybrid classifier based on support vector hidden Markov models was design for implementation semantic mapping and learning...
With rapid development of computer networks, users need a new solution for network security management, aiming at integration. This paper focuses on context-aware alert analysis, which is one of its key functionalities. A practical and efficient approach to guarantee unified representation of context information, background knowledge and attack knowledge for security alerts is still lacking these...
Reports generated by soldiers are common in time-critical military environments. Data fusion systems that attempt to process those reports must maintain the context for each set of observations to avoid inaccurate state estimates. This paper analyzes the selection and assignment of topical context under a Bayesian methodology. We present several techniques to decrease the hypothesis space and heuristics...
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