Latent Semantic Kernels

Kernel methods like support vector machines have successfully been used for text categorization. A standard choice of kernel function has been the inner product between the vector-space representation of two documents, in analogy with classical information retrieval (IR) approaches.Latent semantic indexing (LSI) has been successfully used for IR purposes as a technique for capturing semantic relations between terms and inserting them into the similarity measure between two documents. One of its main drawbacks, in IR, is its computational cost.In this paper we describe how the LSI approach can be implemented in a kernel-defined feature space.We provide experimental results demonstrating that the approach can significantly improve performance, and that it does not impair it.     

XSD: A Hierarchical Access Method for Indexing XML Schemata

Search operations and browsing facilities over an XML document database require special support at the physical level. Typical search operations involve path queries. This paper proposes a hierarchical access method to support such operations and to facilitate browsing. It advocates the idea of searching large XML collections by administering efficiently XML schemata. The proposed approach may be used for indexing XML documents according to their structural proximity. This is obtained by organizing the schemata of a large XML document collection in a hierarchical way by merging structurally close schemata. The proposed structure, which is called XML Schema Directory (XSD), is a balanced tree and it may serve two purposes: (1) to accelerate XML query processing and (2) to facilitate browsing. Received 15 March 2001 / Revised 12 April 2001 / Accepted in revised form 11 May 2001     

Fast Extraction of Semantic Features from a Latent Semantic Indexed Text Corpus

This paper proposes a projection-based symmetrical factorisation method for extracting semantic features from collections of text documents stored in a Latent Semantic space. Preliminary experimental results demonstrate this yields a comparable representation to that provided by a novel probabilistic approach which reconsiders the entire indexing problem of text documents and works directly in the original high dimensional vector-space representation of text. The employed projection index is derived here from the a priori constraints on the problem. The principal advantage of this approach is computational efficiency and is obtained by the exploitation of the Latent Semantic Indexing as a preprocessing stage. Simulation results on subsets of the 20-Newsgroups text corpus in various settings are provided. This revised version was published online in August 2006 with corrections to the Cover Date.     

Reflectance based object recognition

Neighboring points on a smoothly curved surface have similar surface normals and illumination conditions. Therefore, their brightness values can be used to compute the ratio of their reflectance coefficients. Based on this observation, we develop an algorithm that estimates a reflectance ratio for each region in an image with respect to its background. The algorithm is efficient as it computes ratios for all image regions in just two raster scans. The region reflectance ratio represents a physical property that is invariant to illumination and imaging parameters. Several experiments are conducted to demonstrate the accuracy and robustness of ratio invariant.The ratio invariant is used to recognize objects from a single brightness image of a scene. Object models are automatically acquired and represented using a hash table. Recognition and pose estimation algorithms are presented that use ratio estimates of scene regions as well as their geometric properties to index the hash table. The result is a hypothesis for the existence of an object in the image. This hypothesis is verified using the ratios and locations of other regions in the scene. This approach to recognition is effective for objects with printed characters and pictures. Recognition experiments are conducted on images with illumination variations, occlusions, and shadows. The paper is concluded with a discussion on the simultaneous use of reflectance and geometry for visual perception.     

A Formal Model for Video Shot Segmentation and its Application via Animate Vision

The first step in a video indexing process is the segmentation of videos into meaningful parts called shots. In this paper we present a formal model of the video shot segmentation process. Starting from a mathematical characterization of the most common transition effects, a video segmentation algorithm capable to detect both abrupt and gradual transitions is proposed. The proposed algorithm is based on the computation of an arbitrary similarity measure between consecutive frames of a video. The algorithm has been tested adopting a similarity metric based on the Animate Vision theory and results have been reported.     

A new full-text indexing model with low space overhead for chinese text retrieval

Text retrieval systems require an index to allow efficient retrieval of documents at the cost of some storage overhead. This paper proposes a novel full-text indexing model for Chinese text retrieval based on the concept of adjacency matrix of directed graph. Using this indexing model, on one hand, retrieval systems need to keep only the indexing data, instead of the indexing data and the original text data as the traditional retrieval systems always do. On the other hand, occurrences of index term are identified by labels of the so-called s-strings where the index term appears, rather than by its positions as in traditional indexing models. Consequently, system space cost as a whole can be reduced drastically while retrieval efficiency is maintained satisfactory. Experiments over several real-world Chinese text collections are carried out to demonstrate the effectiveness and efficiency of this model. In addition to Chinese, The proposed indexing model is also effective and efficient for text retrieval of other Oriental languages, such as Japanese and Korean. It is especially useful for digital library application areas where storage resource is very limited (e.g., e-books and CD-based text retrieval systems).     

图像检索中的相似性判别及索引方法综述

基于内容的图像检索(CBIR)是对传统信息检索领域的扩展.它采用图像视觉内容的相似性判别进行查询.CBIR涉及到很多科学领域的课题.本文则仅主要综述CBIR技术中的相似性度量方法,索引方式,以及检索性能的评价.最后,分析了该领域现存的问题、最新研究动态及发展方向.     

A hyperplane based indexing technique for high-dimensional data

In this paper, we propose a novel hyperplane based indexing method to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the key dimension based index. Compared with the key dimension concept, the hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Extensive experiments based on two types of real data sets are conducted and the results illustrate a significantly improved filtering efficiency. Because of the feature of hyperplane, the proposed indexing method is only suitable to Euclidean spaces.     

Techniques used and open challenges to the analysis,indexing and retrieval of digital video

Video in digital format is now commonplace and widespread in both professional use, and in domestic consumer products from camcorders to mobile phones. Video content is growing in volume and while we can capture, compress, store, transmit and display video with great facility, editing videos and manipulating them based on their content is still a non-trivial activity. In this paper, we give a brief review of the state of the art of video analysis, indexing and retrieval and we point to research directions which we think are promising and could make searching and browsing of video archives based on video content, as easy as searching and browsing (text) web pages. We conclude the paper with a list of grand challenges for researchers working in the area.     

基于分类标引的文件管理系统

随着海量公开信息源的涌现,大容量存储设备进入个人领域,个人拥有庞大的信息已成为现实.与传统的图书信息不同,个人信息源是根据个人的爱好和需要所构建,因此很难像图书一样制定<中图分类法>来管理个人信息,大量的信息搁置在个人的存储设备上,我们已经无法用传统的手段进行有效管理了,比如目录管理.因此,如何有效地管理个人信息成为当...