Two problems make Spoken Term Detection (STD) particularly challenging under low-resource conditions: the low quality of speech recognition hypotheses, and a high number of out-ofvocabulary (OOV) words. In this paper, we propose an intuitive way to handle OOV terms for STD on word-based Confusion Networks using phonetic similarities, and generalize it into a probabilistic and vocabulary-indepen...

The Protein Information Resource (PIR) provides many databases and tools to support genomic and proteomic research. PIR is a member of UniProt––Universal Protein Resource––the central repository of protein sequence and function, which maintains UniProt Knowledgebase with extensively curated annotation, UniProt Reference databases to speed sequence searches, and UniProt Archive to reflect sequen...

Many scientific experiments are carried out in collaboration with researchers around the world to use existing infrastructures and conduct experiments at massive scale. Data produced by such experiments are thus replicated and cached at multiple geographic locations. This gives rise to new challenges when selecting distributed data and compute resources so that the execution of applications is ...

Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

Ever since the human society has entered era of big data, quantity and type digital learning resources on Internet are increasing exponentially, requirement students for resource retrieval is rise. However, existing methods generally overlook overall knowledge systems that have already possessed, so it’s impossible them to predict students’ path or perform deviation adjustment. In view these is...

The research work described in this thesis focuses on developing a semantic component in conventional Grid architecture to support ontology based representation of Grid resource metadata and to facilitate context based information retrieval that complements Grid schedulers for effective resource management. The previous chapter focussed on semantic representation and discovery of Grid services ...

Metadata represents textual information attached to an image or resource to aid identification and retrieval of that resource. In this paper it is revealed an approach to automate the creation of digital library image metadata embedding semantic and content features. These features will make more precise image content indexing and will allow fast retrieval of images in digital libraries, based ...

This paper presents a data-centric approach to XML information retrieval which benefits from XML document structure and adapts traditional text-centric information retrieval techniques to deal with text content inside XML. We implement our ideas in a configurable, general purpose XML retrieval library which can be tuned to operate on multilingual XML resources with different structure and can b...

Over the past few years, HNC has developed a neural network based, vector space approach to text retrieval. This approach, embodied in a system called MatchPius, allows the user to retrieve information on the basis of meaning and context of a free text query. The MatchPius system uses a neural network based, constrained self-organization technique to learn word stem interrelationships directly ...

The private information retrieval (PIR) primitive has received a significant amount of attention from the scientific community since it was first proposed by Chor et al. with other cryptographic primitives [6, 12] and improved upper bounds [3, 16] have been obtained. In this paper, we continue along this path and give an improved upper bound for information theoretic PIR. Our protocol and proof...