[PDF] Top 20 A Graph-Based Approach to Context Matching

... on context-awareness for pervasive computing [7], certain infrastructures for the processing of context information have been proposed [13, 11, 15, 12, 1, ...the context information ...the ... See full document

... feature-based approach is the Elastic Bunch Graph Matching (EBGM) algorithm [1, 12], which stores spectral information about the neighborhoods of facial features by convolving these areas with ... See full document

... the graph. In the context of above discussion, we exploit the graph to represent any model symbol in our input ...model graph when the given graphical symbol object or input drawing is ... See full document

... The most common algorithm for clustering of local feature descriptors is k-means [11]. For codebook generation was k-means used in many works, e.g. [1,5,12]. The drawback of codebook generation by k-means algorithm is ... See full document

... Exact matching aims at graph isomorphism, where the interest is in an exact matching between nodes and ...the graph isomorphism are based on Tree ...partial matching. Cordella ... See full document

... tion approach for graphs that “divides and conquers” NP -hard ...this approach can be used to solve many graph theoretic problems such as the graph coloring problem, maximal clique problem, ... See full document

... traditional graph kernels can be categorized as random walks-based [5, 20, 55], trees-based [26, 56], and limited-size sub-graphs- based ...walk-based graph kernels have received ... See full document

... of graph similarity has proved to be a challenging problem in structural pattern ...object matching aim at incorporat- ing structural information, advances in measuring graph-similarity are pivotal ... See full document

... in context of other popular natural language appli- cations, such as Machine Translation, Summa- rization, and Question ...their approach on the string regen- eration task and achieve moderate BLEU ... See full document

... The data used for this work consists of histological images provided by The Charit´e Hospital, Berlin. These are biopsy images of the breast tissue. The samples have been stained with the H&E dye. The WSI images are ... See full document

... geometric approach, elastic bunch graph matching, neural network, local binary pattern, automatic local gabor features extraction, principal component analysis with discrete cosine transform, active ... See full document

... people based on their social graph It is not satisfied to user’s preference on friend selection in real ...user based on their ...Friend matching graph find out something life styles of ... See full document

... an approach using a classifier to identify the noisy words candidate for normalization; then using some rules to generate lexical variants and a small normalization ...an approach using an impoverished nor- ... See full document

... Trigui et al. [14] have proposed a new question answering method for Arabic language which aims to answer non-complex questions or questions that required short answers using CLEFF corpus. The proposed method consists of ... See full document

... This paper is organized in nine sections. After the introduction, Section 2 briefly presents pragmatics as the underlying meta-theoretical approach, in the context of the above-mentioned relevance factors. ... See full document

... Each approach (correlation techniques image matching and minutiae-based matching) computes its matching score and the mean of the score from the two approaches is compared with the ... See full document

... Product design is an iterative, complex and decision-making process, performed by designers. It usually starts with recognising and specifying requirements and demands, followed by searching for an optimum solution for ... See full document

... Fuzzy graph theory is finding an increasing number of applications in modeling real time systems where the level of information inherent in the system varies with different levels of ...of matching in fuzzy ... See full document

... Clustering is used to analyze the different grouping of data, similar to the classification, but the grouping has not been defined before data mining tool is executed. Clustering divides the data into groups based ... See full document

... similarity approach, focuses on words by using the term weights that are ...third approach, the N-gram algorithm, deals with the sequences of characters (character level Tri-gram) between sentences of two ... See full document