persian natural language processing (nlp) researchers have many limitations to access linguistic tools which are suitable for text processing. therefore, researchin persian text processing is very limited. since dataset is an important requirement for experiments and their evaluation, we aimed to create appropriate corpora for information retrieval and natural language processing in persian. th...

Effective World Wide Web image retrieval systems are required to locate relevant images as more and more images are used in HTML documents. There are two general approaches to image retrieval: one is based on text descriptions and the other on image contents (low-level features, such as colour and texture). They have their respective strengths and weaknesses. In this paper, we describe how to i...

This article describes the participation of the Image and Text Integration (ITI) group from the U.S. National Library of Medicine (NLM) in the ImageCLEF 2010 medical retrieval track. Our methods encompass a variety of techniques relating to document summarization and textand content-based image retrieval. Our text-based approaches utilize the Unified Medical Language System (UMLS) synonymy to i...

In today’s digital age, the ability to access, analyze and (re)use ever-growing amounts of data is a strategic asset for the broadcasting and media industry. Despite the growing interest around new technologies, archive’s search and retrieval operations are still usually done by means of text-based search over tags and metadata of manually pre-annotated material. This is particularly true becau...

Content-Based Image Retrieval (CBIR), is mainly based on finding images of interest from a large image database using the visual content of the images. Most of the approaches to image retrieval were text-based, where individual images had to be annotated with format. Existing works are based on the performance of a number of clustering algorithms in image retrieval has been analyzed. The propos...

To date, research in image retrieval has focused on the underlying retrieval algorithms, while little research has been focused on the many aspects pertaining to user expectations, user actions and user experiences. It is here postulated that ultimately, it is the user who decides the quality of an image retrieval system based on a match between his/her expectations and system performance. This...

This paper evaluates a system, UBMedTIRS, for retrieval of medical images. The system uses a combination of image and text features as well as mapping of free text to UMLS concepts. UBMedTIRS combines three publicly available tools: a content-based image retrieval system (GIFT), a text retrieval system (SMART), and a tool for mapping free text to UMLS concepts (MetaMap). The system is evaluated...

To solve the problem of indexing collections with diverse text documents, image documents, or documents with both text and images, one needs to develop a model that supports heterogeneous types of documents. In this paper, we show how information theory supplies us with the tools necessary to develop a unique model for text, image, and text/image retrieval. In our approach, for each possible qu...

This paper describes the first participation of the SINAI group of the University of Jaén in TRECVID 2007. We have only participated in the automatic search task. Our approach is a very simple system made up of three main modules: the text-based retrieval subsystem, the image-based retrieval subsystem and the fusion module. We have submitted several runs exploring fusion of both textual and vis...

With the rapid development of computer technology, information and network technology, the traditional retrieval model based on keywords and text description can not meet the needs of mass image retrieval. Therefore, content-based image retrieval has become a hot research topic at home and abroad in recent years. Content-based image retrieval CBIR (Content Based Image Retrieval) is a database t...