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N-dimensional discrete objects can be interpreted as cubical complexes which are suitable for the study of their homology groups in order to understand the original discrete object. The classic approach consists in computing the Normal Smith Form of some matrices associated to the cubical complex. Further approaches deal mainly with a pre-processing of the matrices in order to reduce their size. In...
Being transmitted as part of numerous Internet services, geo location data is increasingly bringing hints of people's real-world activities into Internet traffic. This paper focuses on the discovery of key properties that motivate personal activities - locational interests. We propose and design GeoEcho, a mobile traffic analysis system that extracts and analyses a wealth of latitude-longitude geotag...
The use of word senses in place of surface word forms has been shown to improve performance on many computational tasks, including intelligent web search. In this paper we propose a novel approach to automatic discovery of word senses from raw text, a task referred to as Word Sense Induction (WSI). Almost all the WSI approaches proposed in the literature dealt with monolingual data and only very few...
To access the Internet, companies define a Service Level Agreement (SLA) with Internet Service Providers (ISPs). Nevertheless, the current Internet does not assure Quality of Service (QoS), what points toward the concept of virtual networks (VNs) and software defined network (SDN) to support the Future Internet. Moreover, the VN and SDN approaches can be mixed creating the Virtual Software Defined...
Previous work on snippet generation focused mainly on how to produce one snippet for an individual search result. This paper aims to generate snippets as a comprehensive overview for an entity query (e.g., flu) in a search-result page. Our approach first extracts the attributes (e.g., Symptom and diagnose) of the categories (e.g., Disease) from a community-based question-answering (CQA) website, and...
Network based recommendation systems leverage the topology of the underlying graph and the current user context to rank objects in the database. Random-walk based techniques, such as PageRank, encode the structure of the graph in the form of a transition matrix of a stochastic process from which the significances of the nodes in the graph are inferred. Personalized PageRank (PPR) techniques complement...
In this paper, we present an approach that extracts attributes of open-domain named entities for the Chinese language. The approach contains two steps. The first step consists in an unsupervised technique which captures high frequency attributes from online encyclopedias. The second step discovers uncommon attributes with low frequency. Lastly, an integrated framework is proposed to obtain attributes...
This paper considers the communication and storage costs of emulating atomic (linearizable) multi-writer multi-reader shared memory in distributed message-passing systems. The paper contains two main contributions: 1) We present an atomic shared-memory emulation algorithm that we call Coded Atomic Storage (CAS). This algorithm uses erasure coding methods. In a storage system with 'N' servers that...
Point of interest (POI) categorization is the task of finding of categories of POIs within a document. Because the documents that possess POIs have clue words for identifying POI categories, the task can be solved as document classification. However, this approach misses two crucial factors for identifying the category of a POI. First, the approach pays no attention to onomastic information, even...
This paper presents a novel approach to incorporate multiple contextual factors into a tracking process, for the purpose of reducing false positive detections. While much previous work has focused on improving object detection on static images using context, these have not been integrated into the tracking process. Our hypothesis is that a significant improvement can result from the use of context...
A novel statistical framework for modeling the intrinsic structure of crowded scenes and detecting abnormal activities is presented in this paper. The proposed framework essentially turns the anomaly detection process into two parts, namely, motion pattern representation and crowded context modeling. During the first stage, we averagely divide the spatiotemporal volume into atomic blocks. Considering...
Decision making of worker for appropriate task selection based on workflow is often changed by occurring interruption. Concerned workers of interrupted workflow must optimize workflow to improve consumed time of current tasks by changing engagement of assigned tasks. Although work efficiency is improved by supporting experienced worker for inexperienced worker, time for nurture of inexperienced worker...
Today internet usage has seen tremendous growth. As English is the primary language, documents are mostly available in English language. In India, Hindi is the prevalent language and user wants to access data in Hindi. For the language processing we are required to get the exact sense of polysemous word interpreting the meaning in a particular context. To disambiguate the meaning of the polysemous...
Context information has been widely studied for recognizing collective activities. Most existing works assume that all individuals in a single image share the same activity label. However, in many cases, multiple activities can be coexisted and serve as the context for each other in real-world scenarios. Based on this observation, we propose a novel approach to model both the intra-class and inter-class...
We propose in this paper a framework for the segmentation and classification of document streams. The framework is composed of two modules: segmentation and verification. The two modules use an incremental classifier which learns progressively along the stream. In the segmentation module a relationship between two consecutive pages is classified as either: continuity or rupture. Rupture is synonymous...
The more books a child reads in mother tongue, the better he understands the text although he does not intend to find out the meanings of new words, i.e., using unsupervised learning with previously established constants. We think this is because semantics and syntax of the language emerges in his brain through past sufficient exposure to the language and past interactions with the environment using...
This work exploits the use of a fuzzy many-valued concept analysis for document retrieval to efficiently answer users' queries. For the purpose of visualization, we propose to deal with fuzzy many-valued formal contexts in a tripartite graph with respect to fuzzy triadic document co-similarities. The proposed model aims at describing the documents according to three hierarchical levels. It is based...
In this work we consider a machine learning setting where data are represented as graphs. First, we derive a kernel function which evaluates the similarity between graphs, while capturing pair-wise constraints between graph nodes. Second, we apply it to the problem of classifying collective activities: on this respect we first represent groups of people located in a spatial neighborhood as graphs,...
Semantic relations acquisition is a crucial work in the field of knowledge acquisition. This paper presents a method that acquires semantic relation patterns from large microblog text. It initially analyzes the characteristic of microblog text, and give an algorithm of acquire patterns semi-automatically. Semantic relations are extracted from microblog corpus based on concept recognition and pattern...
Effective information retrieval on handwritten document images has always been a challenging task, especially historical ones. In the paper, we propose a coarse-to-fine handwritten word spotting approach based on graph representation. The presented model comprises both the topological and morphological signatures of the handwriting. Skeleton-based graphs with the Shape Context labelled vertexes are...
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