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This paper examines users behavior in decision making through exploratory search on a keyword map. The keyword map is a kind of interactive information visualization system, which displays relationships between objects (keywords). The system has been studied for analyzing data. The keyword map has a multiple relevance
associated with an image. In our approach, we divide images into small tiles and create visual keywords using a high-dimensional clustering algorithm. These visual keywords act the same as text keywords. One of the challenges of this approach is to identify an appropriate size for visual keywords. In this paper, we report our
vector of the wood image. This keyblock distribution based wood image retrieval algorithm is similar to the keyword based text retrieval algorithm. In the text retrieval algorithm, keyword can be used to represent the content of the text. Similarly, the keyblock in our proposed algorithm can be used to represent the content
We have become able to get enough approvable images of a target object just by submitting its object-name to a conventional keyword-based Web image search engine. However, because the search results rarely include its uncommon images, we can often get only its common images and cannot easily get exhaustive knowledge
where our approach is tested on images retrieved from Google keyword based image search engine. The results show that a combination of our approach as a local image descriptor with another global descriptor outperforms other approaches.
comparison features in real time. In addition the img(Rummager) application can execute a hybrid search of images from the application server, combining keyword information and visual similarity. Also img(Rummager) supports easy retrieval evaluation based on the normalized modified retrieval rank (NMRR) and average precision
currently produce effective annotations for retrieval, while manual annotation is expensive. The proposed approach uses low-level feature similarity to guide the retrieval of keyword annotations and aims to preserve the high quality of manual annotations while reducing the time and cost per annotated video unit. The annotation
In this paper, we propose a multimodal query suggestion method for video search engine which can leverage multimodal processing to improve the quality of search results. When users type general or ambiguous textual queries, our system provides keyword suggestions and representative image examples in an easy-to-use
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
topic, object and attribute dictionaries. Eight kinds of text are extracted as image semantic source from Web pages. Combining with semantic dictionaries, image semantic keywords can be extracted from the eight kinds of text. The strategy of extracting image semantics is better than existing technique, which is better than
The trends in a research field, especially changes in the features over the years, are subjects of interest for many researchers. This paper reports an exploratory analysis of the changes of research topics in an academic field. The target data of the analysis are the author-keywords included in papers presented at a
the age of Big Data where Velocity, Variety and Volume are the challenges, variety of data that include structured as well as unstructured data is the most important issue. Image mining in Big Data is the challenge need to be addressed, so the proposed work compose an image query object, aspect of use, Keywords to
img(Anaktisi) is a C#/.NET content base image retrieval application suitable for the Web. It provides efficient retrieval services for various image databases using as a query a sample image, an image sketched by the user and keywords. The image retrieval engine is powered by innovative compact and effective
system considering artifacts using the self-organizing map with refractoriness makes use of this property in order to retrieve plural similar images. In this image retrieval system, as the image feature, not only color information but also spectrum and keywords are employed. We carried out a series of computer experiments
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