An interactive agent-based system for concept-based web search

Search engines are useful tools in looking for information from the Internet. However, due to the difficulties of specifying appropriate queries and the problems of keyword-based similarity ranking presently encountered by search engines, general users are still not satisfied with the results retrieved. To remedy the above difficulties and problems, in this paper we present a multi-agent framework in which an interactive approach is proposed to iteratively collect a user's feedback from the pages he has identified. By analyzing the pages gathered, the system can then gradually formulate queries to efficiently describe the content a user is looking for. In our framework, the evolution strategies are employed to evolve critical feature words for concept modeling in query formulation. The experimental results show that the framework developed is efficient and useful to enhance the quality of web search, and the concept-based semantic search can thus be achieved.     

D-Index: Distance Searching Index for Metric Data Sets

In order to speedup retrieval in large collections of data, index structures partition the data into subsets so that query requests can be evaluated without examining the entire collection. As the complexity of modern data types grows, metric spaces have become a popular paradigm for similarity retrieval. We propose a new index structure, called D-Index, that combines a novel clustering technique and the pivot-based distance searching strategy to speed up execution of similarity range and nearest neighbor queries for large files with objects stored in disk memories. We have qualitatively analyzed D-Index and verified its properties on actual implementation. We have also compared D-Index with other index structures and demonstrated its superiority on several real-life data sets. Contrary to tree organizations, the D-Index structure is suitable for dynamic environments with a high rate of delete/insert operations.     

Combined Petri net modelling and AI-based heuristic hybrid search for flexible manufacturing systems—part II. Heuristic hybrid search

This two-part paper presents modelling and scheduling approaches of flexible manufacturing systems using Petri nets (PNs) and artificial intelligence (AI)-based heuristic search methods. In Part I, PN-based modelling approaches and basic AI-based heuristic search algorithms were presented. In Part II, a new heuristic function that exploits PN information is proposed. Heuristic information obtained from the PN model is used to dramatically reduce the search space. This heuristic is derived from a new concept, the resource cost reachability matrix, which builds on the properties of B-nets proposed in Part I. Two hybrid search algorithms, (1) an approach to model dispatching rules using analysis information provided by the PN simulation and (2) an approach of the modified stage-search algorithm, are proposed to reduce the complexity of large systems. A random problem generator is developed to test the proposed methods. The experimental results show promising results.     

一种新的半像素快速搜索算法

提出了一种基于在整像素搜索结果的± 1像素邻域内 SAD函数随着与亚像素全局最小点距离的增加而单调增大的半像素两步快速搜索算法。本算法相继在水平和垂直两个共轭的方向上搜索半像素 SAD值的最小点 ,从而得到运动矢量的半像素分量。同时还采用了在每次计算 SAD值之前按需对块进行插值的方法。仿真结果表明本算法在保持图像质量和码流长度基本不变的同时使运算量下降到原来的一半以下。     

Sindi: an intelligent assistant for highway design

We present a system to support highway engineers in the tasks of preliminary highway design. The system is based on the ideas of heuristic search and explicit preference setting. The system has been implemented and installed in a Spanish engineering firm.     

Optimal Ordered Problem Solver

We introduce a general and in a certain sense time-optimal way of solving one problem after another, efficiently searching the space of programs that compute solution candidates, including those programs that organize and manage and adapt and reuse earlier acquired knowledge. The Optimal Ordered Problem Solver (OOPS) draws inspiration from Levin's Universal Search designed for single problems and universal Turing machines. It spends part of the total search time for a new problem on testing programs that exploit previous solution-computing programs in computable ways. If the new problem can be solved faster by copy-editing/invoking previous code than by solving the new problem from scratch, then OOPS will find this out. If not, then at least the previous solutions will not cause much harm. We introduce an efficient, recursive, backtracking-based way of implementing OOPS on realistic computers with limited storage. Experiments illustrate how OOPS can greatly profit from metalearning or metasearching, that is, searching for faster search procedures.     

Searching for information in an online public access catalogue (OPAC): the impacts of information search expertise on the use of Boolean operators

Abstract Boolean systems still constitute most of the installed base of online public access catalogues (OPACs) in the French universities even if many studies have shown that Boolean operators are not frequently used by ‘non‐librarian’ users (by contrast with professional librarians). The first study examined the use of Boolean operators by French university students; In the second study, elaborated to evaluate the impact of information search expertise on this use, Boolean operators are explicitly presented and participants were explicitly invited to use them. We assumed that university students would not frequently use the operators in searching, and that even if they were explicitly invited to make use of them. Results obtained with the first study based on transaction logs analyses confirmed that French university students did not frequently use Boolean operators. The impact of information search expertise, analysed in the second study, compared three levels of expertise: Novice (university students), intermediate (future professional librarians), and expert (professional librarians). Results showed that, even if the three groups were invited to use Boolean operators, this use increased significantly with the level of information search expertise. University students, if they manage procedural functions of connectives in natural language, do not always manage the whole set of procedural functions carried by such connectives when used in the documentary language. So, the relevance of presenting explicit Boolean operators in the OPACs when users are ‘non‐librarians’ is questioned.     

基于遗传算法的落差指数法参数优选

利用遗传算法的全局寻优能力，对落差指数法中的参数进行优化，通过实例分析表明，这种方法是可行的，且能弥补传统作法中的不足，值得推广。     

推进资产证券化发展的本土化进程

在研究资产证券化发展状况的基础上，分析资产证券化在中国现有环境下所面临的许多实施上的障碍，提出了推进资产证券化本土进程的建议．     

N皇后问题的启发式算法探讨

搜索策略的选择与设计是人工智能领域问题求解的核心问题之一,直接影响到问题求解过程中存储空间的占用和计算的复杂性,影响到问题求解的效率。在给出N皇后问题形式化描述和现有搜索算法的基础上,设计了3种解决N皇后问题的启发式算法,并将其与深度优先和宽度优先等搜索策略进行了分析和比较,得出了几点关于设计启发式算法的启示。