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In this paper, we present a new approach for semantic automatic annotation of medical images. Indeed, the proposed approach uses the bag of words model to represent the visual content of the medical image combined with text descriptors based on term frequency-inverse document frequency technique and reduced by latent semantic to extract the co-occurrence between text and visual terms. In a first phase,...
Recently, an increasing number of online news websites have come to provide news browsing and retrieval services. For certain topics, certain news websites may hold sentiment bias, and therefore select and edit information according to their own standpoints before delivering news articles. Lacking conscious awareness of websites' sentiment bias may result in blind obedience to the reported information...
The number of digital photos in the personal computer is exploding. Existing photo annotation and management systems suffer from some problems (some among them are quite serious), which discussed at the beginning of the full paper. Aiming at these problems, this paper proposed a solution based on ontology. First of all, the Family Album ontology is built to organize the domain knowledge and provide...
Traditional information gathering systems are mostly keyword-based that are lack of semantic comprehension and analysis ability and can't guarantee the comprehensiveness and accuracy of information gathering. This paper proposes Chinese patent information gathering model based on domain ontology, which can visualize ontology concept semantic map related to user gathering requirements on the information...
Important and urgent issue of higher education institutions is to provide service to their students, staffs and public with useful education information. In this paper analyzing structure of higher education information, development and improvement of the education information providing service is examined that consists of syllabus database, XML web service, curriculum analyzing system, multivariable...
This paper investigates the capabilities of the Bag-of-Words (BW) method in the 3D shape retrieval field. The contributions of this paper are: 1) the 3D shape retrieval task is categorized from different points of view: specific vs. generic, partial-to-global (PG) vs. global-to-global (GG) retrieval, and articulated vs. non-articulated; 2) The spatial information, which is represented as concentric...
Ordinary users are finding it increasingly difficult to explore the large volumes of diverse data they encounter in their everyday lives. Techniques based on data mining algorithms are useful but they tend to be too complex for casual users to work with effectively. Furthermore, these techniques don't allow the user to engage with the information using semantics meaningful to them. Semantically enriched...
During the last years, a number of search and retrieval methods for audio and visual content were described in literature. Also cross-modal approaches started to emerge recently. All search methods are based on audiovisual fingerprints, which are extracted from the audiovisual data prior to the actual search. Since the most data are available in the compressed domain, they must be decompressed prior...
Information extraction from Web sites is nowadays a relevant problem, usually performed by software modules called wrappers. Introduced the relevant information extraction technology. A combination of HTML pages to extract information of the theme and extract the contents. First of all, to remove noise combination of visual block, the vision-based DOM tree denoising methods to improve the efficiency...
AnHitz is a project promoted by the Basque Government to develop language technologies for the Basque language. The participants in AnHitz are research groups with very different backgrounds: text processing, speech processing and multimedia. The project aims to further develop existing language, speech and visual technologies for Basque: up to now its fruit is a set of 7 different language resources,...
The following topics are dealt with: information retrieval; systems security; knowledge structures; processing methods; information theory and statistics; network theory; information hiding and watermarking; quantum information; data compression and coding; pattern recognition and learning; computer graphics and visualization; computer vision and image processing; decision support and expert systems;...
We present a new method for relevance feedback in image retrieval and a scheme to learn weighted distances which can be used in combination with different relevance feedback methods. User feedback is a crucial step in image retrieval to maximise retrieval performance as was shown in recent image retrieval evaluations. Machine learning is expected to be able to learn how to rank images according to...
In this paper, a new e-map navigation system is designed to provide users with regional navigation services. It provided users keyword search, multiple classification search, and region search, so that userspsila need for diversified searches can be satisfied. Besides, this system applies chromatology to visualize search results, using colors to present landmarks and different degrees of chroma to...
The task of ad hoc photographic image retrieval in ImageCLEF 2007 international benchmark is to retrieve relevant images in the database to the user query formulated as keywords and image examples. This paper presents rich representation and indexing technologies exploited in our system that participated in ImageCLEF 2007. It uses diverse visual content representation, text representation, pseudo-relevance...
The traditional layout of news websites, the combination of classified hierarchical browsing, headline recommendation and keyword-based search, has been used for many years. The keyword-based search is considered to be the most powerful tool for news browsing and retrieval. Unfortunately, the keyword-based query formulation technique is very difficult to use for news audiences because of the mismatch...
In this paper we present an adaptive method for graphic symbol representation based on shape contexts. The proposed descriptor is invariant under classical geometric transforms (rotation, scale) and based on interest points. To reduce the complexity of matching a symbol to a largeset of candidates we use the popular vector model for information retrieval. In this way, on the set of shape descriptors...
We aim to improve the bag-of-visual-words (BOW) model for near-duplicate image retrieval, by introducing a more fine-grained pseudo-relevance feedback process. The BOW method is based on vector quantization of affine invariant descriptors of image patches. Despite its popularity and simplicity, the retrieval performance of BOW is often unsatisfactory due to the large and diverse variations of near-duplicate...
This paper studies the combination of textual and visual information in a database of medical records in order to improve the performance of the multi-modal information retrieval system. The proposed model consists of two subsystems: a content-based information retrieval subsystem that performs the image retrieval and a textual information retrieval subsystem that performs the textual retrieval. The...
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