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Access control models implement mechanisms to restrict access to sensitive data from unprivileged users. Access controls typically check privileges that capture the semantics of the operations they protect. Semantic smells and errors in access control models stem from privileges that are partially or totally unrelated to the action they protect. This paper presents a novel approach, partly based on...
Bug-tracking and issue-tracking systems tend to be populated with bugs, issues, or tickets written by a wide variety of bug reporters, with different levels of training and knowledge about the system being discussed. Many bug reporters lack the skills, vocabulary, knowledge, or time to efficiently search the issue tracker for similar issues. As a result, issue trackers are often full of duplicate...
The goal of the research described here is to present an approach for automating the detection and the extraction of meaning from text using a range of linguistic and ontological techniques, concepts such as the lexico-semantic functions proposed in Meaning-Text Theory by Mel'cuk and the concept of the context. This is motivated, by the fact that, on one hand, these functions enable a better modeling...
Information Systems (IS) research strives for the design of innovative as well as the investigation of existing methods and techniques for information management in organizations. IS methods and techniques can support the automation of operational tasks as well as management tasks in organizations. Furthermore, they offer considerable potential for the automation of research processes in IS research...
In this paper we describes our approach for automatic generation of learning objects' semantic metadata. The extraction process is based on the OBIE (Ontology Based Information Extraction) systems' principles. The input of our approach is a set of IEEE LOM metadata elements in conformance with two requirements. First, each data element must describe the educational content of the learning object....
In this paper we describes our approach for automatic generation of learning objects' semantic metadata. The extraction process is based on the OBIE (Ontology Based Information Extraction) systems' principles. The input of our approach is a set of IEEE LOM metadata elements in conformance with two requirements. First, each data element must describe the educational content of the learning object....
The web is nowadays one of the main information sources, and information search is an important area in which many advances have been registered. One approach to improve web search results is to consider contextual information. Usually, information about context has been provided through user logs on previous searches or the monitoring of clicks on first results, but different approaches can be used...
Topic detection is an hot research in the area of information retrieval. However, the new environment of Internet, the content of which are usually user-generated, asks for new requirements and brings new challenges. Topic detection has to resolve the problem of its lower quality and large amount of noisy. This paper not only provides a solution for detecting hot topics, but also giving its semantic...
Online shopping has developed to a stage where catalogs have become very large and diverse. Thus, it is a challenge to present relevant items to potential customers within a very few interactions. This is even more so when users have no defined shopping objectives but operate in an opportunistic mindset. This problem is often tackled by recommender systems. However, these systems rely on consistent...
Software Product Line has proven to be an effective methodology for developing a diversity of software products at lower costs, in shorter time, and with higher quality. However, the adoption and maintenance of traceability in the context of product lines is considered a difficult task, due to the large number and heterogeneity of assets developed during product line engineering. Furthermore, the...
This paper investigates the role of Distributional Semantic Models (DSMs) in Question Answering (QA), and specifically in a QA system called Question Cube. Question Cube is a framework for QA that combines several techniques to retrieve passages containing the exact answers for natural language questions. It exploits Information Retrieval models to seek candidate answers and Natural Language Processing...
Low information quality is one of the reasons why information extraction initiatives fail. Incomplete information has a pervasive negative impact on downstream processing steps. This work addresses this problem with a novel information extraction approach, which integrates data mining and information extraction methods into a single complementary approach in order to benefit from their respective...
During the software development process, developers are often faced with problem solving situations that motivate the use of the Web to search for information. However, there is a gap between the IDE and the Web, requiring the developers to spend significant time searching for relevant information and navigating through web pages in a Web browser. We propose a tool that aim to aid developers overcoming...
We present a new framework for visualization and retrieval of knowledge organized as a personal semantic web. This framework is an extension of other semantic web technologies and aims to achieve a fast, elegant solution to carrying your knowledge with you. The architecture described has been developed on the Google Android platform and embedded OpenGL. We call this a Personal Knowledge Advantage...
This paper provides an analysis of the main methods for sentence classification in scientific papers and evaluates the feasibility of this technique in unstructured papers in Software Engineering area, in order to automatically find the study results in this area. Tests conducted with the existing methods using unstructured Test Software papers showed results far below those reported by the authors...
This paper addresses the issue of error region detection and characterization in LVCSR transcriptions. It is a well-known phenomenon that errors are not independent and tend to co-occur in automatic transcriptions. We are interested in automatically detecting these so-called error regions. Additionally, in the context of information extraction in TVBN shows, being able to automatically characterize...
In this paper, we propose a semantic query expansion approach by extending the query-regularized mixture model to include latent topics and apply it to spoken documents. We also propose to use context feature vectors for spoken segments to train SVM models to enhance the posterior-weighted normalized term frequencies in lattices. Experiments on Mandarin broadcast news showed that this approach offered...
Author name disambiguation allows to distinguish between two or more authors sharing the same name. In a previous paper, we have proposed a name disambiguation framework in which for each author name in each article we build a context consisting of classification codes, bibliographic references, co-authors, etc. Then, by pair wise comparison of contexts, we have been grouping contributions likely...
This paper introduces a retrieval system based on context rather than content. The system uses a set of vector spaces to represent the different contextual characteristics (position, time, sound environment, etc.). In this model both the current context and the items in the corpus are represented by vectors. We then use vector similarities to identify the relevant items given the context. In order...
In usual Information Retrieval (IR) systems, the user query is represented in the form of a keyword set. Information resources are retrieved according to their similarities to this query. Consequently if query is not declared with appropriate terms, retrieved results would not be satisfactory. Therefore query refinement procedures are incorporated to improve the efficiency of the IR systems.
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