Power domination with bounded time constraints

Based on the power observation rules, the problem of monitoring a power utility network can be transformed into the graph-theoretic power domination problem, which is an extension of the well-known domination problem. A set \(S\) is a power dominating set (PDS) of a graph \(G=(V,E)\) if every vertex \(v\) in \(V\) can be observed under the following two observation rules: (1) \(v\) is dominated by \(S\), i.e., \(v \in S\) or \(v\) has a neighbor in \(S\); and (2) one of \(v\)’s neighbors, say \(u\), and all of \(u\)’s neighbors, except \(v\), can be observed. The power domination problem involves finding a PDS with the minimum cardinality in a graph. Similar to message passing protocols, a PDS can be considered as a dominating set with propagation that applies the second rule iteratively. This study investigates a generalized power domination problem, which limits the number of propagation iterations to a given positive integer; that is, the second rule is applied synchronously with a bounded time constraint. To solve the problem in block graphs, we propose a linear time algorithm that uses a labeling approach. In addition, based on the concept of time constraints, we provide the first nontrivial lower bound for the power domination problem.     

Enabling high-dimensional range queries using <Emphasis Type="Italic">k</Emphasis>NN indexing techniques: approaches and empirical results

Many modern search applications are high-dimensional and depend on efficient orthogonal range queries. These applications span web-based and scientific needs as well as uses for data mining. Although k-nearest neighbor queries are becoming increasingly common due to mobile and geospatial applications, orthogonal range queries in high-dimensional data remain extremely important and relevant. For efficient querying, data is typically stored in an index optimized for either kNN or range queries. This can be problematic when data is optimized for kNN retrieval and a user needs a range query or vice versa. Here, we address the issue of using a kNN-based index for range queries, as well as outline the general computational geometry problem of adapting these systems to range queries. We refer to these methods as space-based decompositions and provide a straightforward heuristic for this problem. Using iDistance as our applied kNN indexing technique, we also develop an optimal (data-based) algorithm designed specifically for its indexing scheme. We compare this method to the suggested naïve approach using real world datasets. The data-based algorithm consistently performs better.     

基于云模型关联规则的企业转型战略风险预警

针对评价指标数据的特点,构造了一种基于云模型的数值型关联规则挖掘算法,并将其运用于企业转型战略风险预警。首先运用云模型约简评价指标;然后,采用属性空间软划分方法对定量型属性的定义域进行划分,使定量型关联规则挖掘转换为定性关联规则挖掘,此基础上提取规则模版;最后采用有规则约束的Apriori算法挖掘云关联规则,并对检验样本风险等级进行判别。实证分析结果表明,与标准BP神经网络模型相比,该模型是一种更为有效和实用的战略风险预警工具。     

A minimized-rule based approach for improving data currency

Repairing obsolete data items to the up-to-date values faces great challenges in the area of improving data quality. Previous methods of data repairing are based on either quality rules or statistical techniques, but both of the two types of methods have their limitations. To overcome the shortages of the previous methods, this paper focuses on combining quality rules and statistical techniques to improve data currency. (1) A new class of currency repairing rules (CRR for short) is proposed to express both domain knowledge and statistical information. Domain knowledge is expressed by the rule pattern, and the statistical information is described by the conditional probability distribution corresponding to each rule. (2) The problem of generating minimized CRRs is studied in both static and dynamic world. In the static world, the problem of generating minimized CRR patterns is proved to be NP-hard, and two approximate algorithms are provided to solve the problem. In dynamic world, methods are provided to update the CRRs without recomputing the whole CRR set in case of data being changed. In some special cases, the updates can be finished in \(O(1)\) time. In both cases, the methods for learning conditional probabilities for each CRR pattern are provided. (3) Based on the CRRs, the problems of finding optimal repairing plans with and without cost budget is studied, and methods are provided to solve them. (4) The experiments based on both real and synthetic data sets show that the proposed methods are efficient and effective.     

基于领域知识和聚类的关联规则深层知识发现研究

本文针对传统关联规则挖掘算法产生大量冗余规则,提出了对关联规则结果进行二次挖掘,并设计了算法对挖掘出的关联规则进行聚类,然后基于已有领域知识对聚类后的关联规则进行新颖度评价,对于新颖度较高价值较大的关联规则可以存储于领域知识库用于决策使用或再次挖掘过程。该算法有效的减少的规则的数量,提高了规则的新颖性和精确度,对商业应用具有很高的价值。文章最后使用UCI开源数据进行了实验分析,并验证了该算法的有效性。     

Equitable colorings of Cartesian products of square of cycles and paths with complete bipartite graphs

A graph G is said to be equitably k-colorable if the vertex set of G can be divided into k independent sets for which any two sets differ in size at most one. The equitable chromatic number of G, \(\chi _{=}(G)\), is the minimum k for which G is equitably k-colorable. The equitable chromatic threshold of G, \(\chi _{=}^{*}(G)\), is the minimum k for which G is equitably \(k'\)-colorable for all \(k'\ge k\). In this paper, the exact values of \(\chi _{=}^{*}(G\Box H)\) and \(\chi _{=}(G\Box H)\) are obtained when G is the square of a cycle or a path and H is a complete bipartite graph.     

On the complete width and edge clique cover problems

A complete graph is the graph in which every two vertices are adjacent. For a graph \(G=(V,E)\), the complete width of G is the minimum k such that there exist k independent sets \(\mathtt {N}_i\subseteq V\), \(1\le i\le k\), such that the graph \(G'\) obtained from G by adding some new edges between certain vertices inside the sets \(\mathtt {N}_i\), \(1\le i\le k\), is a complete graph. The complete width problem is to decide whether the complete width of a given graph is at most k or not. In this paper we study the complete width problem. We show that the complete width problem is NP-complete on \(3K_2\)-free bipartite graphs and polynomially solvable on \(2K_2\)-free bipartite graphs and on \((2K_2,C_4)\)-free graphs. As a by-product, we obtain the following new results: the edge clique cover problem is NP-complete on \(\overline{3K_2}\)-free co-bipartite graphs and polynomially solvable on \(C_4\)-free co-bipartite graphs and on \((2K_2, C_4)\)-free graphs. We also give a characterization for k-probe complete graphs which implies that the complete width problem admits a kernel of at most \(2^k\) vertices. This provides another proof for the known fact that the edge clique cover problem admits a kernel of at most \(2^k\) vertices. Finally we determine all graphs of small complete width \(k\le 3\).     

Approximation for vertex cover in $$\beta $$-conflict graphs

Conflict graph is a union of finite given sets of disjoint complete multipartite graphs. Vertex cover on this kind of graph is used first to model data inconsistency problems in database application. It is NP-complete if the number of given sets r is fixed, and can be approximated within \(2-\frac{1}{2^r}\) (Miao et al. in Proceedings of the 9th international conference on combinatorial optimization and applications, vol 9486. COCOA 2015, New York. Springer, New York, pp 395–408, 2015). This paper shows a better algorithm to improve the approximation for dense cases. If the ratio of vertex not belongs to any wheel complete multipartite graph is no more than \(\beta <1\), then our algorithm will provide a \((1+\beta +\frac{1-\beta }{k})\)-approximation, where k is a parameter related to degree distribution of wheel complete multipartite graph.     

Reconstruction of hidden graphs and threshold group testing

Classical group testing is a search paradigm where the goal is the identification of individual positive elements in a large collection of elements by asking queries of the form “Does a set of elements contain a positive one?”. A graph reconstruction problem that generalizes the classical group testing problem is to reconstruct a hidden graph from a given family of graphs by asking queries of the form “Whether a set of vertices induces an edge”. Reconstruction problems on families of Hamiltonian cycles, matchings, stars and cliques on n vertices have been studied where algorithms of using at most 2nlg?n,(1+o(1))(nlg?n),2n and 2n queries were proposed, respectively. In this paper we improve them to \((1+o(1))(n\lg n),(1+o(1))(\frac{n\lg n}{2}),n+2\lg n\) and n+lg?n, respectively. Threshold group testing is another generalization of group testing which is to identify the individual positive elements in a collection of elements under a more general setting, in which there are two fixed thresholds ? and u, with ?<u, and the response to a query is positive if the tested subset of elements contains at least u positive elements, negative if it contains at most ? positive elements, and it is arbitrarily given otherwise. For the threshold group testing problem with ?=u?1, we show that p positive elements among n given elements can be determined by using O(plg?n) queries, with a matching lower bound.     

Exemplar or matching: modeling DCJ problems with unequal content genome data

The edit distance under the DCJ model can be computed in linear time for genomes with equal content or with Indels. But it becomes NP-Hard in the presence of duplications, a problem largely unsolved especially when Indels (i.e., insertions and deletions) are considered. In this paper, we compare two mainstream methods to deal with duplications and associate them with Indels: one by deletion, namely DCJ-Indel-Exemplar distance; versus the other by gene matching, namely DCJ-Indel-Matching distance. We design branch-and-bound algorithms with set of optimization methods to compute exact distances for both. Furthermore, median problems are discussed in alignment with both of these distance methods, which are to find a median genome that minimizes distances between itself and three given genomes. Lin–Kernighan heuristic is leveraged and powered up by sub-graph decomposition and search space reduction technologies to handle median computation. A wide range of experiments are conducted on synthetic data sets and real data sets to exhibit pros and cons of these two distance metrics per se, as well as putting them in the median computation scenario.     

基于意外度的关联规则深层知识发现及应用研究

为了弥补传统关联规则挖掘产生大量冗余规则、难以直接用于决策支持的不足,本文提出了一种基于用户已有知识的规则意外度评价方法,并在此基础上设计了基于意外度的深层关联规则挖掘算法。算法的优点在于能够将用户已知的规则作为领域知识加入到数据挖掘过程从而有效过滤和已知规则相近的冗余规则,并且可以将新得到的规则加入知识库中实现知识的积累和重用。最后本文采用一个商场数据验证了该算法的有效性,并且对具有回馈模式的关联规则在商品促销中的作用进行了分析。     

Cost sharing and strategyproof mechanisms for set cover games

We develop for set cover games several general cost-sharing methods that are approximately budget-balanced, in the core, and/or group-strategyproof. We first study the cost sharing for a single set cover game, which does not have a budget-balanced mechanism in the core. We show that there is no cost allocation method that can always recover more than $\frac{1}{\ln n}$ of the total cost and in the core. Here n is the number of all players to be served. We give a cost allocation method that always recovers $\frac{1}{\ln d_{\mathit{max}}}$ of the total cost, where d _max is the maximum size of all sets. We then study the cost allocation scheme for all induced subgames. It is known that no cost sharing scheme can always recover more than $\frac{1}{n}$ of the total cost for every subset of players. We give an efficient cost sharing scheme that always recovers at least $\frac{1}{2n}$ of the total cost for every subset of players and furthermore, our scheme is cross-monotone. When the elements to be covered are selfish agents with privately known valuations, we present a strategyproof charging mechanism, under the assumption that all sets are simple sets; further, the total cost of the set cover is no more than ln?d _max times that of an optimal solution. When the sets are selfish agents with privately known costs, we present a strategyproof payment mechanism to them. We also show how to fairly share the payments to all sets among the elements.     

Partitioning dense uniform hypergraphs

Let \(r\ge 3\) and \(k\ge 2\) be fixed integers, and let H be an r-uniform hypergraph with n vertices and m edges. In 1997, Bollobás and Scott conjectured that H has a vertex-partition into k sets with at most \(m/k^r+o(m)\) edges in each set. So far, this conjecture was confirmed when \(r=3\) or \(m=\Omega (n^{r-1+o(1)})\). In this paper, we show that it holds for \(m=\Omega (n^{r-3+\epsilon })\) for any \(\epsilon >0\).     

Approximation algorithms for minimum weight partial connected set cover problem

In the Minimum Weight Partial Connected Set Cover problem, we are given a finite ground set \(U\), an integer \(q\le |U|\), a collection \(\mathcal {E}\) of subsets of \(U\), and a connected graph \(G_{\mathcal {E}}\) on vertex set \(\mathcal {E}\), the goal is to find a minimum weight subcollection of \(\mathcal {E}\) which covers at least \(q\) elements of \(U\) and induces a connected subgraph in \(G_{\mathcal {E}}\). In this paper, we derive a “partial cover property” for the greedy solution of the Minimum Weight Set Cover problem, based on which we present (a) for the weighted version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are adjacent in \(G_{\mathcal {E}}\) (the Minimum Weight Partial Connected Vertex Cover problem falls into this range), an approximation algorithm with performance ratio \(\rho (1+H(\gamma ))+o(1)\), and (b) for the cardinality version under the assumption that any pair of sets in \(\mathcal {E}\) with nonempty intersection are at most \(d\)-hops away from each other (the Minimum Partial Connected \(k\)-Hop Dominating Set problem falls into this range), an approximation algorithm with performance ratio \(2(1+dH(\gamma ))+o(1)\), where \(\gamma =\max \{|X|:X\in \mathcal {E}\}\), \(H(\cdot )\) is the Harmonic number, and \(\rho \) is the performance ratio for the Minimum Quota Node-Weighted Steiner Tree problem.     

Incremental Facility Location Problem and Its Competitive Algorithms

We consider the incremental version of the k-Facility Location Problem, which is a common generalization of the facility location and the k-median problems. The objective is to produce an incremental sequence of facility sets F ₁?F ₂?????F _n , where each F _k contains at most k facilities. An incremental facility sequence or an algorithm producing such a sequence is called c -competitive if the cost of each F _k is at most c times the optimum cost of corresponding k-facility location problem, where c is called competitive ratio. In this paper we present two competitive algorithms for this problem. The first algorithm produces competitive ratio 8α, where α is the approximation ratio of k-facility location problem. By recently result (Zhang, Theor. Comput. Sci. 384:126–135, 2007), we obtain the competitive ratio \(16+8\sqrt{3}+\epsilon\). The second algorithm has the competitive ratio Δ+1, where Δ is the ratio between the maximum and minimum nonzero interpoint distances. The latter result has its self interest, specially for the small metric space with Δ≤8α?1.     

An approximation algorithm for maximum weight budgeted connected set cover

This paper studies approximation algorithm for the maximum weight budgeted connected set cover (MWBCSC) problem. Given an element set \(X\), a collection of sets \({\mathcal {S}}\subseteq 2^X\), a weight function \(w\) on \(X\), a cost function \(c\) on \({\mathcal {S}}\), a connected graph \(G_{\mathcal {S}}\) (called communication graph) on vertex set \({\mathcal {S}}\), and a budget \(L\), the MWBCSC problem is to select a subcollection \({\mathcal {S'}}\subseteq {\mathcal {S}}\) such that the cost \(c({\mathcal {S'}})=\sum _{S\in {\mathcal {S'}}}c(S)\le L\), the subgraph of \(G_{\mathcal {S}}\) induced by \({\mathcal {S'}}\) is connected, and the total weight of elements covered by \({\mathcal {S'}}\) (that is \(\sum _{x\in \bigcup _{S\in {\mathcal {S'}}}S}w(x)\)) is maximized. We present a polynomial time algorithm for this problem with a natural communication graph that has performance ratio \(O((\delta +1)\log n)\), where \(\delta \) is the maximum degree of graph \(G_{\mathcal {S}}\) and \(n\) is the number of sets in \({\mathcal {S}}\). In particular, if every set has cost at most \(L/2\), the performance ratio can be improved to \(O(\log n)\).     

The 3-rainbow index and connected dominating sets

A tree in an edge-colored graph is said to be rainbow if no two edges on the tree share the same color. An edge-coloring of \(G\) is called a 3-rainbow coloring if for any three vertices in \(G\), there exists a rainbow tree connecting them. The 3-rainbow index \(rx_3(G)\) of \(G\) is defined as the minimum number of colors that are needed in a 3-rainbow coloring of \(G\). This concept, introduced by Chartrand et al., can be viewed as a generalization of the rainbow connection. In this paper, we study the 3-rainbow index by using connected 3-way dominating sets and 3-dominating sets. We show that for every connected graph \(G\) on \(n\) vertices with minimum degree at least \(\delta \, (3\le \delta \le 5)\), \(rx_{3}(G)\le \frac{3n}{\delta +1}+4\), and the bound is tight up to an additive constant; whereas for every connected graph \(G\) on \(n\) vertices with minimum degree at least \(\delta \, (\delta \ge 3)\), we get that \(rx_{3}(G)\le \frac{\ln (\delta +1)}{\delta +1}(1+o_{\delta }(1))n+5\). In addition, we obtain some tight upper bounds of the 3-rainbow index for some special graph classes, including threshold graphs, chain graphs and interval graphs.     

Two extremal problems related to orders

We consider two extremal problems related to total orders on all subsets of \({\mathbb N}\). The first one is to maximize the Lagrangian of hypergraphs among all hypergraphs with m edges for a given positive integer m. In 1980’s, Frankl and Füredi conjectured that for a given positive integer m, the r-uniform hypergraph with m edges formed by taking the first m r-subsets of \({\mathbb N}\) in the colex order has the largest Lagrangian among all r-uniform hypergraphs with m edges. We provide some partial results for 4-uniform hypergraphs to this conjecture. The second one is for a given positive integer m, how to minimize the cardinality of the union closure families generated by edge sets of the r-uniform hypergraphs with m edges. Leck, Roberts and Simpson conjectured that the union closure family generated by the first m r-subsets of \({\mathbb N}\) in order U has the minimum cardinality among all the union closure families generated by edge sets of the r-uniform hypergraphs with m edges. They showed that the conjecture is true for graphs. We show that a similar result holds for non-uniform hypergraphs whose edges contain 1 or 2 vertices.     

Separating NE from some nonuniform nondeterministic complexity classes

We investigate the question whether NE can be separated from the reduction closures of tally sets, sparse sets and NP. We show that (1) \(\mathrm{NE}\not\subseteq R^{\mathrm{NP}}_{n^{o(1)}-T}(\mathrm{TALLY})\); (2) \(\mathrm{NE}\not\subseteq R^{SN}_{m}(\mathrm{SPARSE})\); (3) \(\mathrm{NEXP}\not\subseteq \mathrm{P}^{\mathrm{NP}}_{n^{k}-T}/n^{k}\) for all k≥1; and (4) \(\mathrm{NE}\not\subseteq \mathrm{P}_{btt}(\mathrm{NP}\oplus\mathrm{SPARSE})\). Result (3) extends a previous result by Mocas to nonuniform reductions. We also investigate how different an NE-hard set is from an NP-set. We show that for any NP subset A of a many-one-hard set H for NE, there exists another NP subset A′ of H such that A′? A and A′?A is not of sub-exponential density.