Parameterized top-k algorithms pdf

Trajectory compression algorithms enable efficient transmission, storage, and processing of trajectory data by eliminating redundant information. Computer science masters theses computer science theses and. If thats correct, then start with the first 10 items in each list will allow you to generate the correct output if you only want unique items in the output, but the inputs might contain duplicates, then you need 10 unique items in each list. Design and implementation of applications over delay tolerant networks for disaster and battlefield environment, karthikeyan sachidanandam.

First, we propose the best position algorithm bpa which executes topk queries much more efficiently than ta. The linq library currently does not have a dedicated top k implementation. Apr 24, 2010 the database community has devoted extensive amount of efforts to indexing and querying temporal data in the past decades. In this paper, we propose two new algorithms for processing topk queries over sorted lists. Cfvs is the connected variant of the classical feedback vertex set problem and is defined as follows. Reduction to a problem kernel then means to replace instance i,k by a. The goal is to ensure ps victory by shifting p higher. The pdf of the random variable maxx, y the max imum of the two. A correction for this article has been appended to the pdf file. We study the recently introduced connected feedback vertex set cfvs problem from the viewpoint of parameterized algorithms. Efficient parameterized algorithms for biopolymer structuresequence alignment article pdf available in ieeeacm transactions on computational biology and bioinformatics 34. Some generic indexing structures based on rtrees do support. In particular, we present a linear time algorithm for the top k problem which has a competitive ratio of equation. Contents preface xiii i foundations introduction 3 1 the role of algorithms in computing 5 1.

Parameterized top k algorithms seem to have an increasing demand in recent research and applications in computational sciences. Our algorithm is a parameterized algorithm 11, in which the naturally small parameter k determined by a statistical cutoff re. Distributed topk monitoring stanford infolab stanford university. Since we are counting the top k, i believe that we could devise an algorithm that scales o k in space. On the complexity of the star phub center problem with parameterized triangle inequality. This comprehensive textbook presents a clean and coherent account of most fundamental tools and techniques in parameterized algorithms and is a selfcontained guide to the area.

Parameterized algorithms for generalized traveling salesman. This book constitutes the refereed proceedings of the 21st annual european symposium on algorithms, esa 20, held in sophia antipolis, france, in september 20 in the context of the combined conference algo 20. Parameterized algorithms for conflictfree colorings of graphs. In the shift bribery problem, we are given an election, a preferred candidate p, and a budget. One of the most popular strategies to cope with nphard problems is that of parameterized complexity 12, 17, where the core idea is to identify a parameter k. Approximation and parameterized algorithms for common subtrees and edit distance between unordered trees tatsuya akutsu, daiji fukagawa, magnus m.

While a large number of compression algorithms have been developed, there is no comprehensive and convenient. Parameterized complexity of committee elections with. Prices matter for the parameterized complexity of shift. We then present an approach to approximate different ranking functions using our parameterized ranking functions, and to learn a ranking function from user preferences section 5. We present novel algorithms based on generating functions that enable highly ef. Optimal algorithms for selecting topk combinations of. Anytime measures for topk algorithms semantic scholar. Thus, even for sparse graphs, these algorithms require quadratic running time in the worst case, which is prohibitive for large networks.

Srinivas aluru and in the cheriton school of computer science, university of waterloo, canada with prof. In section 4, we present our generating functionsbased algorithms for ranking. In particular, we show that for a large class of wellknown np optimization problems, there are parameterized topk algorithms that produce the best k solutions for the problems in feasible amount. The area of parameterized approximation seeks to combine approximation and parameterized algorithms to obtain, e. More precisely, given any time instance t, the query asks for the top k objects at time t with respect to some score attribute.

The book covers many of the recent developments of the field, including application of important. Whenk 1, it is known asa minimum costgroupsteinertree problem which is npcomplete. Goodrich department of computer science university of california, irvine. In contrast, our algorithm solves the generalized topk. In parameterized complexity we concentrate on some distinguished parameter of the problem, such as the number of candidates or the number of voters. Cheriton school of computer science university of waterloo ecient processing of topk queries is a crucial requirement in many interactive environments that involve massive amounts of data.

A good choice of the parameter c depends on the skew of the score. Intuitively, the policy gradient objective either increases the probability of the action when the return is higher than expected a t0 or decreases the probability when the return is lower than expected a t algorithms in the literature, such as lenstras algorithm for integer linear programming 319 or the disjoint paths algorithm of robertson and seymour 402, it was only in the late 1980s that downey and ellofws 149, building on joint work with langston 180, 182, 183, proposed the systematic exploration of parameterized algorithms. Intuitively, knnoptimal performs a range search with a variable shrinking. Html and pdf documents obtained from a crawl of the. In this paper we initiate a study of anytime topk algorithms. The new algorithm with the time complexity oktn2 is more ef. Multiquery optimization for continuous topk query workloads by avani shastri a thesis submitted to the faculty of the worcester polytechnic institute in partial ful. A survey of topk query processing techniques in relational database systems ihab f. If i understand your question correctly, the correct output is the top 10 items, irrespective of the list from which each came. Top k queries join queries product combinations combination ranking abstract given a relation that contains main products and a set of relations corresponding to accessory products that can be combined with a main product, the exploratory top k join query retrieves the k best combinations of main and accessory products based on user preferences. As one of the core operations in data retrieval, we study top k queries with crowdsourcing, namely crowdenabled top k queries. Intuitively, treewidth measures how well the structure of a graph can be captured by a treelike. In recent years, crowdsourcing has emerged as a new computing paradigm for bridging the gap between human and machinebased computation.

We then present an approach to approximate different ranking functions using our parameterized ranking functions, and to learn a ranking. Apr 19, 2018 if one were not interested in approximation algorithms but still wanted to use top k counting rules, then one might seek fixedparameter tractable algorithms. In section 6, we explore the connection between prf. A general framework of our parameterized topk algorithms can be divided into two components. Data structures and algorithms in java 6th edition pdf free. Siam journal on computing society for industrial and.

A parameterized topk algorithm a for q is an algorithm that in an instance x, k of q produces the k best solutions for x, k. Before joining ucf, i have worked as a research scientistpostdoc in the school of computational science and engineering, georgia institute o f technology, atlanta with prof. Keywords and phrases parameterized complexity, election control, optimal attack, optimal defense 1 introduction the problem of election control asks if it is possible for an external agent, usually. Data structures and algorithms in java sixth edition michael t. I am an assistant professor in the department of computer science at university of central florida. Pdf efficient parameterized algorithms for biopolymer. Programs usually use the orderby function followed by the take function. Our key algorithm is an onlogn algorithm for ranking using a prfe function over lowcorrelation datasets. Advanced techniques for improving canonical genetic programming, adam tyler harter. The treewidth of a graph is one of the most frequently used tools in parameterized algorithms. Parameterized algorithms and complexity is a natural way to cope with problems.

Our approach to parameterized top k algorithms proceeds in two stages. Comparing top k lists siam journal on discrete mathematics. This was formulated to minimize the number of questions under the constraint of the number of rounds. This book constitutes the refereed proceedings of the 21st annual european symposium on algorithms, esa 20, held in sophia antipolis, france, in september 20 in the context of the combined confere.

Besides the applications to the task of identifying good notions of dissimilarity between two top k lists, our results imply polynomialtime constantfactor approximation algorithms for the rank aggregation problem with respect to a large class of distance measures. Halldorsson, atsuhiro takasu, keisuke tanaka pages 1022. In this paper, we studied the problem of answering top k queries with crowds. Siam journal on discrete mathematics society for industrial. Theoretical computer science vol 470, pages 1120 28. New methods in parameterized algorithms and complexity ucsb. Processing topk queries using the nave algorithm is very expensive for. To the best of our knowledge, this is the first paper proposing parallel algorithms to process topk. We propose two greedy algorithms for the optimal defense problem and empirically show that they perform effectively on reasonable voting pro. To address this problem, we modeled a parameterized framework with two parameters b and r.

We observe that the number of keywords, l,is small, and propose a novel parameterized solution, with l. The currently best algorithms in practical applications for computing the closeness for all nodes exactly in unweighted graphs are based on breadthfirst search bfs from every node. Computing top k closeness centrality faster in unweighted. In particular, we show that for a large class of wellknown np optimization problems, there are parameterized top k algorithms that produce the best k solutions for the problems in feasible amount. Evolved parameterized selection for evolutionary algorithms, samuel nathan richter.

1441 1251 746 469 1223 312 608 420 549 751 840 924 1480 1602 13 177 930 722 159 152 1567 1035 1093 1015 1464 1292 1529 1295 611 625 602 232 83 1011 163 227 1147 63 516 29 585