IDL Compiler API Design, Application and Validation Based on XML API

In order to adapt different languages and platforms, the paper discusses how to process and validate IDL symbol table and intermediate code by XML API. It puts emphasis on IDL AP1 extension towards DOM API based on the idea of combining XML with IDL compilers. At last, the IDL compiler designing framework based on XML AP! is given, in which compiler front end can be managed and validated by some XML techniques and tools, IDL API can be validated on the basis of test, so IDL intermediate code is provided with maintainability, portability and generation. IDL compiler can be developed and extended by XML-based API, which realizes versatility and portability of modern compiler.

A Novel Forensic Computing Model

According to the requirement of computer forensic and network forensic, a novel forensic computing model is presented, which exploits XML/OEM/RM data model, Data fusion technology, forensic knowledgebase, inference mechanism of expert system and evidence mining engine. This model takes advantage of flexility and openness, so it can be widely used in mining evidence.

Similarity Measurement of Web Sessions Based on Sequence Alignment

The task of clustering Web sessions is to group Web sessions based on similarity and consists of maximizing the intra-group similarity while minimizing the inter-group similarity. The first and foremost question needed to be considered in clustering Web sessions is how to measure the similarity between Web sessions. However, there are many shortcomings in traditional measurements. This paper introduces a new method for measuring similarities between Web pages that takes into account not only the URL but also the viewing time of the visited Web page. Then we give a new method to measure the similarity of Web sessions using sequence alignment and the similarity of Web page access in detail Experiments have proved that our method is valid and efficient.

Efficient Evaluation of Monitoring Top-t Most Influential Places

The continuous top-t most influential place （CTtMIP） query is defined formally and solved efficiently in this paper. A CTtMIP query continuously monitors the t places with the maximum influence from the set of places, where the influence of a place is defined as the number of its bichromatic reverse k nearest neighbors （BRkNNs）. Two new metrics and their corresponding rules are introduced to shrink the search region and reduce the candidates of BRkNNs checked. Extensive experiments confirm that our proposed approach outperforms the state-of-the-art competitor significantly.

Identifying Composite Crosscutting Concerns with Scatter-Based Graph Clustering

Identifying composite crosscutting concerns（CCs） is a research task and challenge of aspect mining.In this paper,we propose a scatter-based graph clustering approach to identify composite CCs.Inspired by the state-of-the-art link analysis tech-niques,we propose a two-state model to approximate how CCs tangle with core modules.According to this model,we obtain scatter and centralization scores for each program element.Espe-cially,the scatter scores are adopted to select CC seeds.Further-more,to identify composite CCs,we adopt a novel similarity measurement and develop an undirected graph clustering to group these seeds.Finally,we compare it with the previous work and illustrate its effectiveness in identifying composite CCs.

基于ISA网络的视频人体行为分类识别

采用基于独立子空间分析(ISA)模型与神经网络理论形成的ISA深度网络模型特征提取方法,并结合数据预处理方法、K-means聚类方法以及支持向量机(SVM)分类器等实现对视频人体行为的分类识别.将本研究方法应用到Hollywood2人体行为数据集上进行人体行为识别实验,并与其他常用人体行为特征提取和识别方法进行对比,实验结果验证了本研究方法在人体行为分类识别中的有效性.

一种融合本体与条件随机场的视频语义提取方法

从时空角度结合条件随机场模型及本体概念,提出了一种视频语义特征提取方法,其中包括视频低层特征模型参数估计(model parameter estimation,MPE)算法和高层对象语义模型更新(model update,MU)算法。该方法可以实现视频语义概念本体的自动提取和标注,为语义特征提取及分析提供支持。实验结果表明,该方法提升了视频语义特征提取的精确率和召回率。

Image retrieval based on multi-concept detector and semantic correlation

With the rapid development of future network, there has been an explosive growth in multimedia data such as web images. Hence, an efficient image retrieval engine is necessary. Previous studies concentrate on the single concept image retrieval, which has limited practical usability. In practice, users always employ an Internet image retrieval system with multi-concept queries, but, the related existing approaches are often ineffective because the only combination of single-concept query techniques is adopted. At present semantic concept based multi-concept image retrieval is becoming an urgent issue to be solved. In this paper, a novel Multi-Concept image Retrieval Model(MCRM) based on the multi-concept detector is proposed, which takes a multi-concept as a whole and directly learns each multi-concept from the rearranged multi-concept training set. After the corresponding retrieval algorithm is presented, and the log-likelihood function of predictions is maximized by the gradient descent approach. Besides, semantic correlations among single-concepts and multiconcepts are employed to improve the retrieval performance, in which the semantic correlation probability is estimated with three correlation measures, and the visual evidence is expressed by Bayes theorem, estimated by Support Vector Machine(SVM). Experimental results on Corel and IAPR data sets show that the approach outperforms the state-of-the-arts. Furthermore, the model is beneficial for multi-concept retrieval and difficult retrieval with few relevant images.

A Modularity Analysis Method for Forum Situation Prediction

A forum is a social network that consists of posters and the following comments made by netizens. Generally speaking, forum topics are evolving over time dynamically. In this paper, based on time series analysis and matrix modularity analysis, a novel prediction method is proposed through investigating the correlating influence of three key measurements： relationship strength, pillars, and change frequency of a forum topic. The method demonstrates that there exist some macroscopic and potential laws for forum situation prediction. Extensive experiments over large many datasets show the efficiency and effectiveness of the algorithms.

Editorial

This issue of Science China Physics, Mechanics ＆ Astronomy celebrates the Centenary of Einstein＇s General Theory of Rela- tivity, which changed the way humanity understood the concepts of space, time and matter. Prior to 1915 Einstein had intro- duced his theory of Special Relativity, and Minkowski had introduced the spacetime metric. General Relativity overthrew the Newtonian idea that space, time and matter were independent, replacing it with the idea that space, time and matter are inex- tricably linked. Within a year of the publication of General Relativity came Schwartzchild＇s exact solution of Einstein＇s field equations which describes the spacetime structure of black holes. In 1916 and 1918 Einstein showed that his theory predicted the existence of gravitational waves. Within 7 years, in 1922, Friedmann published a solution for Einstein＇s field equations applied to a homogeneous universe, uncovering the basic physics of Big Bang cosmology.