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Document categorization is the process of assigning pre-defined categories to textual documents. State-of-the art approaches have modelled documents in terms of corpus-length long vectors and viewed the problem only from a syntactic perspective. We develop a general measure to estimate the semantic closeness of documents by utilizing the semantic relatedness of the most discriminative individual words...
Specication guided falsication methods for hybrid systems have recently demonstrated their value in detecting design errors in models of safety critical systems. In specication guided falsication, the correctness problem, i.e., does the system satisfy the specication, is converted into an optimization problem where local negative minima indicate design errors. Due to the complexity of the resulting...
Cross-domain resource and infrastructure federation has gained more and more attention in the fields of Cloud and Future Internet (FI) testbeds. But, interoperable monitoring data exchange across heterogeneous domains remains a challenge due to the variety and heterogeneity of the used tools and interfaces. Many efforts have been made to define common data models and protocols but are task or domain...
Context: Software source code is frequently changed for fixing revealed bugs. These bug-fixing changes might introduce unintended system behaviors, which are inconsistent with scenarios of existing regression test cases, and consequently break regression testing. For validating the quality of changes, regression testing is a required process before submitting changes during the development of software...
The renewed interest for physical-layer security techniques has put forward a new role for error-control codes. In addition to ensuring reliability, carefully designed codes have been shown to provide a level of information-theoretic secrecy, by which the amount of information leaked to an adversary may be controlled. The ability to achieve information-theoretic secrecy relies on the study of alternative...
In this paper, we investigate the task of paraphrase identification in Vietnamese documents, which identify whether two sentences have the same meaning. This task has been shown to be an important research dimension with practical applications in natural language processing and data mining. We choose to model the task as a classification problem and explore different types of features to represent...
WiFi networks are becoming increasingly ubiquitous. In addition to providing network connectivity, WiFi finds applications in areas such as indoor and outdoor localisation, home automation, and physical analytics. In this paper, we explore the semantics of one key attribute of a WiFi network, SSID name. Using a dataset of approximately 120,000 WiFi access points and their corresponding geo-locations,...
Person re-identification is the task of associating people across cameras with non-overlapping view field. Two key aspects of Person re-identification are the feature representation and metric learning. The feature representation employed should be both discriminative and invariant, which is also our considering in this paper. To enhance person re-identification performance, we propose to combine...
This paper reports robustness comparison of clustering-based multi-label classification methods versus non-clustering counterparts for multi-concept associated image and video annotations. In the experimental setting of this paper, we adopted six popular multi-label classification algorithms, two different base classifiers for problem transformation based multi-label classifications, and three different...
An important aspect when sharing images in social networks is the tags the images are annotated with. Another closely related problem is the ability to successfully recommend images to users. An automatic image annotation and recommendation system is proposed based on Parallel Factor Analysis 2 (PARAFAC2). Here, PARAFAC2 is applied to a collection of three matrices, namely the image-feature matrix,...
Semantic mapping is the incremental process of “mapping” relevant information of the world (i.e., spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine. Current research focuses on learning the semantic of environments based on their spatial location, geometry and appearance. Many methods to tackle this problem have been proposed, but the...
This paper presents the challenges related to the different points of view (System model, safety, 3D, topology, multiphysics, multi-agent, metrics) of MBSE design of mechatronic systems. To tackle this complexity and better take into account, simultaneously, these different points of view, we propose to define an ontology based on a mechatronic design process modeling. Finally, we also define the...
We propose an algorithm that enables robots to improve their spatial-semantic representation of an environment by engaging users in dialog during a guided tour. The algorithm selects the best information gathering actions in the form of targeted questions that reduce the ambiguity over the grounding of user-provided natural language descriptions (e.g., “The kitchen is down the hallway”). These questions...
In Software Product Line (SPL) engineering, Feature Models (FMs) are widely used to capture and manage variability in a sound and organized fashion. Though semantics, notations and reasoning support are well established, maintaining large FMs is still an open problem. As large FMs naturally contain different concerns, some related to domains, others being inherently cross-cutting ones, it is challenging...
Existed methods of code clones detection have some restrictions. Textual and lexical approaches cannot detect strongly modified fragments of code. Syntactic and metrics based approaches detect strong modifications with low accuracy. On the contrary, semantic approach accurately detects the cloned fragments of code with small changes as well as the strongly modified ones. Methods based on this approach...
Real databases often consist of hundreds of innerlinked tables, which makes posing a complex join query a really hard task for common users. Join query recommendation is an effective technique to help users formulate better join queries and explore their information demand. In this paper, we propose a novel approach to automatically create join query recommendations based on path frequency. Our approach...
Spatial features has gained attention in CBIR researches as a mean to represent image properties. These features, presented via Spatial Relation Features (SRF) such left, right, on and in can provide fine queries to locate object location as well as its relation with other object within an image. Although spatial features play an important, yet, there is still less effort done to collect them in proper...
Person re-identification is an important computer vision task with many applications in areas such as surveillance or multimedia. Approaches relying on handcrafted image features struggle with many factors (e.g. lighting, camera angle) which lead to a large variety in visual appearance for the same individual. Features based on semantic attributes of a person's appearance can help with some of these...
Interaction analysis is defined as the generation of semantic descriptions from machine perception. This can be achieved through a combination of fuzzy metric temporal logic (FMTL) and situation graph trees (SGTs). We extended the FMTL/SGT framework with modules for clustering and parameter learning and we showed their advantages. The contributions of this paper are 1) the combination of FMTL/SGT...
Plagiarism is an illicit act which has become a prime concern mainly in educational and research domains. This deceitful act is usually referred as an intellectual theft which has swiftly increased with the rapid technological developments and information accessibility. Thus the need for a system/ mechanism for efficient plagiarism detection is at its urgency. In this paper, an investigation of different...
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