基于隐含语义的个性化信息检索

随着互连网上信息资源的极度膨胀，出现了各种各样的信息搜集工具给用户提供信息服务，但是目前的信息搜集系统在给用户提供信息服务时，很难根据用户的个人信息实现个性化的信息服务，不同的用户相同的查询请求，返回的查询结果是相同的，这给用户的使用带来了很大的不便，而隐含语义检索(LSI)可以利用关键词之间的语义信息完成信息的搜索。提出了利用LSI来进行个性化信息检索算法的几种实现方法，并通过实验验证了算法的有效性。     

Image indexing and retrieval based on color histograms

While general object recognition is difficult, it is relatively easy to capture various primitive properties such as color distributions, prominent regions and their topological features from an image and use them to narrow down the search space when attempts to retrieving images by contents from an image database are made.In this paper, we present an image database in which images are indexed and retrieved based on color histograms. We first address the problems inherent in color histograms created by the conventional method, and then propose a new method to create histograms which are compact in size and insensitive to minor illumination variations such as highlight, shape, and etc. A powerful indexing scheme where each histogram of an image is encoded into a numerical key, and stored in a two-layered tree structure is introduced. This approach turns the problem of histogram matching, which is computation intensive, into index key search, so as to realize quick data access in a large scale image database. Two types of user interfaces, Query by user provided sample images, and Query by combination of the system provided templates, are provided to meet various user requests. Various experimental evaluations exhibit the effectiveness of the image database system.     

Image indexing and retrieval based on vector quantization

To effectively utilize information stored in a digital image library, effective image indexing and retrieval techniques are essential. This paper proposes an image indexing and retrieval technique based on the compressed image data using vector quantization (VQ). By harnessing the characteristics of VQ, the proposed technique is able to capture the spatial relationships of pixels when indexing the image. Experimental results illustrate the robustness of the proposed technique and also show that its retrieval performance is higher compared with existing color-based techniques.     

Design issues of multimedia information indexing and retrieval systems

Multimedia information indexing and retrieval systems are required to manage and use ever increasing multimedia information effectively and efficiently. This paper first provides an over-view of general capabilities and architecture of multimedia information indexing and retrieval systems, and then discusses a number of main design issues including data modelling, user interface, feature extraction, indexing, feature similarity measures and quality of service guarantees.     

A visual user interface for map information retrieval based onsemantic significance

User-interface facilities of a map information system HI-MAP that provide visual feedback to the user are presented. The facilities include semantic panning and zooming, overlaying of thematic maps, etc., and are available through an interactive menu system. HI-MAP retrieves map elements in a specified region on the basis of their relevance and their categorical classification. It has a data structure that includes logical and physical hierarchies for the management of semantic relationships and graphic map elements. The software for implementing these facilities is well modularized, and a variety of interfacing modes can be realized by simple communication between modules. The system contributes toward a reduction of the difficulties in obtaining what is really required from databases     

基于内容的视频快速索引*

提出了一种基于内容的视频索引方法。将视频内容分为人脸(face)、风景(landscape)和运动目标(object motion)三种模式,实现手机平台上的快速视频索引。 首先在不同模式下用滑动窗口的方法计算出每个时间片的感兴趣程度。在face模式下,利用水平投影直方图分析人脸所在的大致位置,综合统计人脸区域的变化;在Landscape模式下,进行HSV空间的直方图统计;在object motion模式下,用基于光流的跟踪算法得出目标的运动矢量。在用户选择对应的模式后,对每个时间片内的视频求得各前后帧的     

Semantic indexing of Arabic texts for information retrieval system

As part of information retrieval systems (IRS) and in the context of the use of ontologies for documents and queries indexing, we propose and evaluate in this paper the contribution of this approach applied to Arabic texts. To do this we indexed a corpus of Arabic text using Arabic WordNet. The disambiguation of words was performed by applying the Lesk algorithm. The results obtained by our experiment allowed us to deduct the contribution of this approach in IRS for Arabic texts.     

Combining spatial and colour information for content based image retrieval

Colour is one of the most important features in content based image retrieval. However, colour is rarely used as a feature that codes local spatial information, except for colour texture. This paper presents an approach to represent spatial colour distributions using local principal component analysis (PCA). The representation is based on image windows which are selected by two complementary data driven attentive mechanisms: a symmetry based saliency map and an edge and corner detector. The eigenvectors obtained from local PCA of the selected windows form colour patterns that capture both low and high spatial frequencies, so they are well suited for shape as well as texture representation. Projections of the windows selected from the image database to the local PCs serve as a compact representation for the search database. Queries are formulated by specifying windows within query images. System feedback makes both the search process and the results comprehensible for the user.     

A content based image information retrieval and video thumbnail extraction framework using SOM

Searching an image or a video in a huge volume of graphical data is a tedious time-consuming process. If this search is performed using the conventional element matching technique, the complexity of the search will render the system useless. To overcome this problem, the current paper proposes a Content-Based Image Retrieval (CBIR) and a Content-Based Video Retrieval (CBVR) technique using clustering algorithms based on neural networks. Neural networks have proved to be quite powerful for dimensionality reduction due to their parallel computations. Retrieval of images in a large database on the basis of the content of the query image has been proved fast and efficient through practical results. Two images of the same object, but taken from different camera angles or have rotational and scaling transforms is also matched effectively. In medical domain, CBIR has proved to be a boon to the doctors. The tumor, cancer etc can be easily deducted comparing the images with normal to the images with diseases. Java and Weka have been used for implementation. The thumbnails extracted from the video facilitates the video search in a large videos database. The unsupervised nature of Self Organizing Maps (SOM) has made the software all the more robust.

     

基于DICOM文本与内容的医学图像检索系统研究

为辅助医师从海量医学图像中快速查找所需图像,提出了一种将DICOM文本信息和图像底层特征相结合的医学图像检索方法。从DICOM图像的文件头中提取文本信息,进行图像预筛选,提取图像的纹理及形状特征,通过设定权重将这两种特征相结合,进行基于内容的图像检索。实验结果表明,综合纹理和形状特征的检索方法优于单一特征检索方法,联合DICOM文本信息和底层特征的方法能明显提高检索的效能,使检索结果更接近于人的视觉理解。     

Multimedia information retrieval based on pairwise comparison and its application to visual search

Finding a way to elicit user preferences in the context of multimedia information retrieval is an important issue that remains to be solved. Users are not usually able to find a sought after image or provide an example of what they want. One of several possible methods that might be used to solve this problem involves reasoning about user queries through the assessment of several samples. In this article we propose a method by which user queries are retrieved based on the pairwise comparison of sample alternatives. Pairwise comparison was originally designed for the ranking of alternatives. In our method we rank criteria according to their importance for the user and then use this information to retrieve relevant records from the database. The method was implemented in Matlab and tested on the Microsoft Research Cambridge Image Database.     

A new indexing method based on word proximity for Chinese text retrieval

This paper propsed a novel text representation and matching scheme for Chinese text retrieval.At present,the indexing methods of chinese retrieval systems are either character-based or word-based.The character-based indexing methods,such as bi-gram or tri-gram indexing,have high false drops due to the mismatches between queries and documents.On the other hand,it‘s difficult to efficiently identify all the proper nouns,terminology of different domains,and phrases in the word-based indexing systems.The new indexing method uses both proximity and mutual information of the word paris to represent the text content so as to overcome the high false drop,new word and phrase problems that exist in the character-based and word-based systems.The evaluation results indicate that the average query precision of proximity-based indexing is 5.2% higher than the best results of TREC-5.     

A visual language compiler for information retrieval by visualreasoning

When a database increases in size, retrieving the data becomes a major problem. An approach based on data visualization and visual reasoning is described. The main idea is to transform the data objects and present sample data objects in a visual space. The user can use a visual language to incrementally formulate the information retrieval request in the visual space. A prototype system is described with the following features: (1) it is built on top of the SIL-ICON visual language compiler and therefore can be customized for different application domains; (2) it supports a fuzzy icon grammar to define reasonable visual sentences; (3) it incorporates a semantic model of the database for fuzzy visual query translation; and (4) it incorporates a VisualNet which stores the knowledge learned by the system in its interaction with the user so that the VisualReasoner can adapt its behavior     

Multi-joint histogram based modelling for image indexing and retrieval

This paper presents a novel approach for image retrieval, named multi-joint histogram based modelling (MJHM), in which the joint correlation histograms are constructed between the motif and texton maps. Firstly, the quantized image is divided into non-overlapping 2 × 2 grids. Then each grid is replaced by a scan motif and texton values to construct the transformed motif and texton maps (images) respectively. The motif transformed map minimizes the local gradient and texton transformed map identifies the equality of grayscales while traversing the 2 × 2 grid. Finally, the correlation histograms are constructed between the transformed motif and texton maps. The performance of the proposed method (MJHM) is tested by conducting two experiments on Corel-5K and Corel-10K benchmark databases. The results after investigation show significant improvements in terms of precision, average retrieval precision (ARP), recall and average retrieval rate (ARR) as compared to multi-texton histogram (MTH), smart content based image retrieval system (CMCM) and other state-of-the-art techniques for image retrieval.     

基于视觉一致性的图像检索

提出一种新的彩色图像分割方法,将图像分割成具有明显视觉一致性的区域,这种一致性能够模拟人观察图像时的视觉感受,例如图像中的一片区域具有相同的颜色、纹理。对这样的一致性区域建立特征描述符,如颜色编码、连通系数、面积比例,其中颜色编码是通过将像素在HSI颜色空间中量化得到,进而为整幅图像建立特征描述;然后将这种特征描述用于图像的检索。实验结果表明,这种方法不仅能够很好地模拟图像所带给人的视觉感受,而且对具有视觉一致性的图像检索效果也有很好的表现。     

一种新型的基于样本的Web信息检索技术

本文提出了一种新型的基于样本的信息检索方法.首先,通过归纳学习不同站点的样本页面,生成抽取规则;然后,用这些规则把不同站点页面的信息抽取出来,把这些信息整合到一个虚拟的关系数据库中;最后,可以直接检索数据库中的信息.从而,一次可以检索多个站点的信息,大大提高了检索效率.