In this paper a new method for image retrieval using high level semantic features is proposed. It is based on extraction of low level color, shape and texture characteristics and their conversion into high level semantic features using fuzzy production rules, derived with the help of an image mining technique. DempsterShafer theory of evidence is applied to obtain a list of structures containin...

This paper attempts to discuss the evolution of the retrieval techniques focusing on development, challenges and trends of the image retrieval. It highlights both the already addressed and outstanding issues. The explosive growth of image data leads to the need of research and development of Image Retrieval. However, Image retrieval researches are moving from keyword, to low level features and ...

Managing software quality in a technology-driven, medium or small size development organization, characterized by a very heterogeneous environment, is a complex task that requires particular attention in order to be effective. This paper describes a process improvement experiment (PIE) targeted to the introduction of software reuse practices as an approach to software quality. Main objectives o...

This year the Blog Track contained two tasks: Top Stories Identification and Faceted Blog Distillation Tasks. Our submissions for both tasks are described below. In this, our first entry into the blog track, we explore various strategies (latent Dirichlet relevance model, URL based ranking, query expansion etc.) for both tasks. We first indexed the blog data with Lucene and identified occurrenc...

A key challenge in the semantic web is the mapping between different concepts. Many techniques for such mapping exist, but most of them induce a one-to-one mapping, which does not seem to correspond to real world problems. This project proposes a new approach, which tries to use the power of machine learning, and in particular classification algorithms, to solve the mapping task. It introduces ...

OBJECTIVE This study aimed to examine semantic processing features in individuals with and without schizotypal personality disorder (SPD) features. METHODS An implicit semantic task was used to examine the automatic spreading semantic activation process which is relatively free from the influence of attention. An explicit semantic task was used to examine the controlled semantic processing wh...

We propose a novel zero-shot learning method for semantic utterance classification (SUC). It learns a classifier f : X → Y for problems where none of the semantic categories Y are present in the training set. The framework uncovers the link between categories and utterances through a semantic space. We show that this semantic space can be learned by deep neural networks trained on large amounts...

Extraction and utilization of high-level semantic features are critical for more effective video retrieval. However, the performance of video retrieval hasn’t benefited much despite of the advances in high-level feature extraction. To make good use of high-level semantic features in video retrieval, we present a method called pointwise mutual information weighted scheme(PMIWS). The method makes...

This paper describes an approach for defining robust, application-independent confidence measures for dialogue systems. A concept-level confidence score is computed using a Multi-Layer Perceptron (MLP) classifier trained to discriminate between correct and incorrect concepts. Three types of concept-level confidence features are considered: features based on the confidence score of the underlyin...

In this paper, a new method for heuristics and intermediate features based image retrieval is proposed. Heuristic features are identified and directly stored into the database and easily retrieved also. An algorithm is used to convert low level features hue, saturation and intensity in HSI space to semantic based color names. Images can be retrieved by these semantic color names. For semantics ...