For a broad-topic and ambiguous query, different users may have different search goals when they submit it to a search engine. The inference and analysis of user search goals can be very useful in improving search engine relevance and user experience. In this paper, we propose a novel approach to infer user search goals by […]
Privacy Preserving Network Publication against Structural Attacks
Privacy is one of the major concerns when publishing or sharing social network data for social science research and business analysis. Recently, researchers have developed privacy models similar to k-anonymity to prevent node re-identification through structure information. However, even when these privacy models are enforced, an attacker may still be able to infer one’s private […]
Mining Distance-Based Outliers from Categorical Data
Outlier detection can usually be considered as a pre-processing step for locating, in a data set, those objects that do not conform to well-defined notions of expected behavior. It is very important in data mining for discovering novel or rare events, anomalies, vicious actions, exceptional phenomena, etc. We are investigating outlier detection for categorical data […]
MIN-MAX: A Counter-Based Algorithm for Regular Expression Matching
We propose an NFA-based algorithm called MIN-MAX to support matching of regular expressions (regexp) composed of Character Classes with Constraint Repetitions (CCR). MIN-MAX is well suited for massive parallel processing architectures, such as FPGAs, yet it is effective on any other computing platform. In MIN-MAX, each active CCR engine (to implement one CCR term) evaluates […]
Tractable Reasoning and Efficient Query Answering in Description Logics
The current trend for building an ontology-based data management system (DMS) is to capitalize on efforts made to design a preexisting well-established DMS (a reference system). The method amounts to extracting from the reference DMS a piece of schema relevant to the new application needs—a module—, possibly personalizing it with extra constraints w.r.t. the application […]
A neural model of contour integration in the primary visual cortex
Algorithms that encode images using a sparse set of basis functions have previously been shown to explain aspects of the physiology of a primary visual cortex (V1), and have been used for applications, such as image compression, restoration, and classification. Here, a sparse coding algorithm, that has previously been used to account for the response […]
Medical image enhancement using resolution synthesis
We introduce the bilateral filter BF is the same bilateral filter we use in the HSF for improved resolution synthesis For picture blocks, BR(Bayesian reconstruction) simply uses the conventional JPEG decoder to decode the blocks. RS is a classification based image interpolation scheme which achieves optimal interpolation by training from image pairs at low resolution […]
Improved binary partition tree construction for hyperspectral images
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image-processing tools. Hyperspectral imaging enables the characterization of regions based on their spectral properties which provides a rich amount of information. This paper proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation relying on the […]
Reconstruction of missing blocks in image transmission by using self-embedding
A new model of the content reconstruction problem in self-embedding systems, based on an erasure communication channel. In addition to the content hashes for authentication purposes, an encoder embeds in the image a reconstruction reference, which describes the content, and which can be used by a dedicated decoder to restore the tampered image fragments. Hence […]
Learning Horizontal Connections In A Sparse Coding Model Of Natural Images
Image prior models based on sparse and redundant representations are attracting more and more attention in the field of image restoration. The conventional sparsity-based methods enforce sparsity prior on small image patches independently. Unfortunately, these works neglected the contextual information between sparse representations of neighboring image patches . Sparse coding of image patches extracted from […]
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