现代信息检索理论架构研究

信息作为一种新的资源,对当代经济和社会的发展起着非常重要的作用,如何高效快捷地利用现代信息是当前我国信息检索领域研究的重要问题。阐述了现代信息检索理论架构研究的前提,分析了当前主要的信息检索理论,探讨了网络信息检索的主要方法。     

一种基于用户偏好和反馈的页面排序技术

传统的排名方法没有考虑用户的喜好、反馈和用户兴趣,很难满足用户的个性化需求.针对这个问题,提出一种新的网页排名方法,将网页的相似度、链接结构信息、用户偏好及用户反馈相结合进行页面排名.实验结果表明,改进的排序算法在一定程度上帮助用户提高检索网页的质量,最大限度地满足用户的需求.     

导航系统视觉快速跟踪方法

提出了一种图象搜索的方法 ,适用于变化的环境 ,通过灰度值偏移校正二维阈值化和噪声滤波的方法能有效排除由于光源所引起的各种干扰 .本方法处理速度快 ,满足自引导车实时跟踪和导航的需要     

A search technique for global optimization in a chaotic environment

We describe a new algorithm which uses the trajectories of a discrete dynamical system to sample the domain of an unconstrained objective function in search of global minima. The algorithm is unusually adept at avoiding nonoptimal local minima and successfully converging to a global minimum. Trajectories generated by the algorithm for objective functions with many local minima exhibit chaotic behavior, in the sense that they are extremely sensitive to changes in initial conditions and system parameters. In this context, chaos seems to have a beneficial effect: failure to converge to a global minimum from a given initial point can often be rectified by making arbitrarily small changes in the system parameters.     

二维椭圆型方程反问题中优化算法的比较

近年来，决定椭圆型方程系数反问题在地磁、地球物理、冶金和生物等实际问题上有着广泛的应用．本文讨论了二维的决定椭圆型方程系数反问题的数值求解方法．由误差平方和最小原则，这个反问题可化为一个变分问题，并进一步离散化为一个最优化问题，其目标函数依赖于要决定的方程系数．本文着重考察非线性共轭梯度法在此最优化问题数值计算中的表现，并与拟牛顿法作为对比．为了提高算法的效率我们适当选择加快收敛速度的预处理矩阵．同时还考察了线搜索方法的不同对优化算法的影响．数值实验的结果表明，非线性共轭梯度法在这类大规模优化问题中相对于拟牛顿法更有效．     

Searching in trees

In (Discrete Math. 17 (1977)181) Rivest introduced the search complexity of binary trees and proved that among all binary trees with a fixed search complexity the smallest ones are the so-called Fibonacci trees. This result is extended for q-trees. The structure of the smallest q-trees is again Fibonacci-like but more complicated than in the binary case. In addition an upper bound for the asymptotic growth of these trees is given.     

Local approximations for maximum partial subgraph problem

We deal with MAXH₀-FREE PARTIAL SUBGRAPH. We mainly prove that 3-locally optimum solutions achieve approximation ratio (δ₀+1)/(B+2+ν₀), where B=max_v∈Vd_G(v), δ₀=min_v∈V(H0)d_H0(v) and ν₀=(|V(H₀)|+1)/δ₀. Next, we show that this ratio rises up to 3/(B+1) when H₀=K₃. Finally, we provide hardness results for MAXK₃-FREE PARTIAL SUBGRAPH.     

Heuristic Algorithms and Scatter Search for the Cardinality Constrained P||Cmax Problem

We consider the generalization of the classical P||C_max problem (assign n jobs to m identical parallel processors by minimizing the makespan) arising when the number of jobs that can be assigned to each processor cannot exceed a given integer k. The problem is strongly NP-hard for any fixed k > 2. We briefly survey lower and upper bounds from the literature. We introduce greedy heuristics, local search and a scatter search approach. The effectiveness of these approaches is evaluated through extensive computational comparison with a depth-first branch-and-bound algorithm that includes new lower bounds and dominance criteria.     

Combining Swaps and Node Weights in an Adaptive Greedy Approach for the Maximum Clique Problem

In this work, the NP-hard maximum clique problem on graphs is considered. Starting from basic greedy heuristics, modifications and improvements are proposed and combined in a two-phase heuristic procedure. In the first phase an improved greedy procedure is applied starting from each node of the graph; on the basis of the results of this phase a reduced subset of nodes is selected and an adaptive greedy algorithm is repeatedly started to build cliques around such nodes. In each restart the selection of nodes is biased by the maximal clique generated in the previous execution. Computational results are reported on the DIMACS benchmarks suite. Remarkably, the two-phase procedure successfully solves the difficult Brockington-Culberson instances, and is generally competitive with state-of-the-art much more complex heuristics.