Edit Costs Research Articles

Computation of graph edit distance: Reasoning about optimality and speed-up

Bipartite graph matching has been demonstrated to be one of the most efficient algorithms to solve error-tolerant graph matching. This algorithm is based on defining a cost matrix between the whole nodes of both graphs and solving the nodes' correspondence through a linear assignment method (for instance, Hungarian or Jonker–Volgenant methods). Recently, two versions of this algorithm have been published called Fast Bipartite and Square Fast Bipartite. They compute the same distance value than Bipartite but with a reduced runtime if some restrictions on the edit costs are considered. In this paper, we do not present a new algorithm but we compare the three versions of Bipartite algorithm and show how the violation of the theoretically imposed restrictions in Fast Bipartite and Square Fast Bipartite do not affect the algorithm's performance. That is, in practice, we show that these restrictions do not affect the optimality of the algorithm and so, the three algorithms obtain similar distances and recognition ratios in classification applications although the restrictions do not hold. Moreover, we conclude that the Square Fast Bipartite with the Jonker–Volgenant solver is the fastest algorithm.

Dynamic edit distance table under a general weighted cost function

We discuss the problem of edit distance computation under a dynamic setting, where one of the two compared strings may be modified by single-character edit operations and we wish to keep the edit distance information between the strings up-to-date. A previous algorithm by Kim and Park (2004) [6] solves a more limited problem where modifications can be done only at the ends of the strings (so-called decremental or incremental edits) and the edit operations have (essentially) unit costs. If the lengths of the two strings are m and n, their algorithm requires O(m+n) time per modification. We propose a simple and practical algorithm that (1) allows arbitrary non-negative costs for the edit operations and (2) allows the modifications to be done at arbitrary positions. If the latter string is modified at position j⋆, our algorithm requires O(min⁡{rc(m+n),mn}) time, where r=min⁡{j⋆,n−j⋆+1} and c is the maximum edit operation cost. This equals O(m+n) in the simple decremental/incremental unit cost case. Our experiments indicate that the algorithm performs much faster than the theoretical worst-case time limit O(mn) in the general case with arbitrary edit costs and modification positions. The main practical limitation of the algorithm is its Θ(mn) memory requirement for storing the edit distance information.

Speeding up Fast Bipartite Graph Matching Through a New Cost Matrix

Bipartite (BP) has been seen to be a fast and accurate suboptimal algorithm to solve the Error-Tolerant Graph Matching problem. Recently, Fast Bipartite (FBP) has been presented that obtains the same distance value and node labelings but in a reduced time. Both algorithms approximate the quadratic problem in a linear problem and they do it through a specific cost matrix. FBP imposes the Edit costs to be defined such as the Edit distance is a distance function. Originally, the Hungarian method was used but it has been seen the Jonker–Volgenant linear solver obtains similar results than the Hungarian method but with an important run time reduction. Nevertheless, this second solver has some convergence problems on some specific cost matrices. The aim of this paper is to define a new cost matrix such that the Jonker–Volgenant solver converges and the matching algorithm obtains the same distance value than the BP algorithm.

Fast computation of Bipartite graph matching

We present a new algorithm to compute the Graph Edit Distance in a sub-optimal way. We demonstrate that the distance value is exactly the same than the one obtained by the algorithm called Bipartite but with a reduced run time. The only restriction we impose is that the edit costs have to be defined such that the Graph Edit Distance can be really defined as a distance function, that is, the cost of insertion plus deletion of nodes (or arcs) have to be lower or equal than the cost of substitution of nodes (or arcs). Empirical validation shows that higher is the order of the graphs, higher is the obtained Speed up.

Sequence Comparison Applied to Correction and Markup of Multi-Word Responses

In some instructional situations, such as foreign language dictation, the degree of correctness of a student's text response can be determined without reference to grammar and semantics by comparison with a target string provided by a course author. The standard sequence comparison procedure, which assesses the distance between two strings in terms of edit costs, makes demands on machine time proportional to the product of the string lengths. This characteristic renders it impractical for real-time correction of multi-word responses on current instructional computer systems. We present a much faster but nonadmissible version of other applications, thereby bringing the technique within range of current microcomputers. The usual method for generating markup for single word responses does not generalize well to multi-word responses because it fails to recognize word boundaries, and will sometimes suggest edits that seem unnatural to users. We propose an extension which attends to word boundaries and thereby recommends corrections that appear more reasonable.

Improving Transliteration Mining by Integrating Expert Knowledge with Statistical Approaches

paper contributes a study of methods for integrating human expert knowledge with machine learning approaches for determining phonetic similarity of word pairs. A method is proposed which allows a human to provide a structure for the edit costs that are based around a phonetically-motivated model of phoneme sound groups, and the machine to determine precise values for these costs within two different frameworks based on stochastic edit distance: a method based on one-to-one expectation maximization (EM) alignment and a Bayesian many-to-many alignment approach. A preliminary study is within the context of cross-language word similarity in transliteration mining. The experiments were performed on a Myanmar-English mining task; the principle approach is expected to be most useful for low-resource language pairs, where human expert knowledge can compensate for a lack of data resources. The results show that the approach outperforms baseline systems based on only human knowledge and only on machine learning. This approach showed the choice of edit cost is a strong factor in determining the performance of the edit-distance-based techniques used in these experiments. The learned edit costs consistently outperformed a simple set of plausible costs selected by a human expert. Furthermore, providing a structure to the weights for the machine learning process reduced the number of parameters to be learned simplifying and speeding up the learning task. This method is expected to mitigate issues with data sparseness when learning models for low-resource languages. The reduction in the number of model parameters led to improvements in recall in these experiments, even though the model was considerably smaller, validating the choice of structure.

THE NEW EMERGENT MULTIMEDIA CONTENT AND DIGITAL RIGHTS MANAGEMENT

Culture in the digital environment, after a drastic reduction in the cost of storage and editing, allowed remixing and faster sharing than in the analog age. The result of this new content is no longer published or presented through traditional forms known in the analog era. The old gatekeepers are no longer gatekeepers. Thus, copyright, once valid, conflicts with the dynamics of the digital culture. Digital Rights Management, used by a company as a tool, is an option to control and to guarantee economic interests. How can it become sustainable in order to create, to consume, to publish and to share multimedia content in this landscape?

ON THE GRAPH EDIT DISTANCE COST: PROPERTIES AND APPLICATIONS

We model the edit distance as a function in a labeling space. A labeling space is an Euclidean space where coordinates are the edit costs. Through this model, we define a class of cost. A class of cost is a region in the labeling space that all the edit costs have the same optimal labeling. Moreover, we characterize the distance value through the labeling space. This new point of view of the edit distance gives us the opportunity of defining some interesting properties that are useful for a better understanding of the edit distance. Finally, we show the usefulness of these properties through some applications.

Improving Multilingual Semantic Interoperation in Cross-Organizational Enterprise Systems Through Concept Disambiguation

For the multilingual semantic interoperations in cross-organizational enterprise systems and e-commerce systems, semantic consistency is a research issue that has not been well resolved. This paper contributes to improving multilingual semantic interoperation by proposing a concept-connected near synonym (NSG) framework for concept disambiguation. NSG framework provides a vocabulary preprocessing process of collaborative vocabulary editing, which further ensures semantically consistent vocabulary for building semantically consistent business processes and documents between context-different information systems. The vocabulary preprocessing offered by NSG automates the process of finding potential near synonym sets and identifying collaboratively editable near synonym sets. The realization of NSG framework includes a probability model that computes concept values between concepts based on a newly introduced semantic relatedness method-SRCT. In this paper, SRCT-based methods are implemented and compared with some existing semantic relatedness methods. Experiments have shown that SRCT-based methods outperform the existing methods. This paper has made an improvement on the existing methods of semantic relatedness and reduces the collaboration cost of collaborative vocabulary editing.

Advances in targeted genome editing

New technologies have recently emerged that enable targeted editing of genomes in diverse systems. This includes precise manipulation of gene sequences in their natural chromosomal context and addition of transgenes to specific genomic loci. This progress has been facilitated by advances in engineering targeted nucleases with programmable, site-specific DNA-binding domains, including zinc finger proteins and transcription activator-like effectors (TALEs). Recent improvements have enhanced nuclease performance, accelerated nuclease assembly, and lowered the cost of genome editing. These advances are driving new approaches to many areas of biotechnology, including biopharmaceutical production, agriculture, creation of transgenic organisms and cell lines, and studies of genome structure, regulation, and function. Genome editing is also being investigated in preclinical and clinical gene therapies for many diseases.

From maximum common submaps to edit distances of generalized maps

Generalized maps are widely used to model the topology of nD objects (such as images) by means of incidence and adjacency relationships between cells (vertices, edges, faces, volumes, etc.). In this paper, we introduce distance measures for comparing generalized maps, which is an important issue for image processing and analysis. We introduce a first distance measure which is defined by means of the size of a largest common submap. This distance is generic: it is parameterized by a submap relation (which may either be induced or partial), and by weights to balance the importance of darts with respect to seams. We show that this distance measure is a metric. We also introduce a map edit distance, which is defined by means of a minimum cost sequence of edit operations that should be performed to transform a map into another map. We relate maximum common submaps with the map edit distance by introducing special edit cost functions for which they are equivalent. We experimentally evaluate these distance measures and show that they may be used to classify meshes.

Balance Sheet Outlier Detection Using a Graph Similarity Algorithm

Graph similarity measurement has been used in many applications, such as computational biology, text mining, pattern recognition, and computer vision. In this paper, we apply similarity measurement on graphs to measure structural differences in financial statements. Unconventional financial statement structures may potentially reveal deceptive intention of hiding certain information while making technically correct financial statements. Furthermore, unconventional financial statements may also lead to investment opportunities if legitimacy is not questioned. We construct an algorithm based on the metric of string edit distance as an approximation of graph similarity, and apply the Levenshtein algorithm with modified string edit costs to measure string edit distance. We demonstrate the effectiveness of this algorithm in capturing the sensitive changes of balance sheet structures by applying the algorithm in two experiments. The first experiment shows the algorithm is sensitive to all three basic edits (namely deletion, insertion and substitution) on a particular balance sheet, and the second experiment shows more than 90% clustering accuracy on real balance sheets.

Reassortment Networks for Investigating the Evolution of Segmented Viruses

Many viruses of interest, such as influenza A, have distinct segments in their genome. The evolution of these viruses involves mutation and reassortment, where segments are interchanged between viruses that coinfect a host. Phylogenetic trees can be constructed to investigate the mutation-driven evolution of individual viral segments. However, reassortment events among viral genomes are not well depicted in such bifurcating trees. We propose the concept of reassortment networks to analyze the evolution of segmented viruses. These are layered graphs in which the layers represent evolutionary stages such as a temporal series of seasons in which influenza viruses are isolated. Nodes represent viral isolates and reassortment events between pairs of isolates. Edges represent evolutionary steps, while weights on edges represent edit costs of reassortment and mutation events. Paths represent possible transformation series among viruses. The length of each path is the sum edit cost of the events required to transform one virus into another. In order to analyze tau stages of evolution of n viruses with segments of maximum length m, we first compute the pairwise distances between all corresponding segments of all viruses in O(m2n2) time using dynamic programming. The reassortment network, with O(taun2) nodes, is then constructed using these distances. The ancestors and descendents of a specific virus can be traced via shortest paths in this network, which can be found in O(taun3) time.

Developing Qualitative Research Analyses

All MS Word window, function and command names are in italic. An analysis is a process that contains stages (or phases). Each stage contains one or more procedures that contain steps. Use these terms consistently to avoid confusion and enable replication of your study. To quickly structure an analysis, use process and procedure tables, which you can later convert into paragraphs after you've entered information in each table cell. The tables help ensure that you do not (i) report findings in the analysis and (ii) overlook vital information-because if a cell is empty, then information is probably missing. Note: Some authors find table lines helpful during information development, while others find them distracting. So insert whatever makes the tables usable for you. Open p_templates, select Save As…, and give the file a new name (e.g., DP_anlys). Note: Table-generating macros are an alternative to saving templates in .dot or .doc formats, but instructions for creating and using them are beyond this article's scope. Describe data analysis in the process table in the new file, for example: Creating and using procedure templates Describe the procedure, for example: Study and correct the overall process description and each procedure after you describe each stage in detail to (i) ensure that you've documented everything and (ii) generate ideas for developing transition sentences. Note: Never write two consecutive headings without text in between-a convention that some non-native English speakers use. A heading indicates what the information below it is about. So either delete one heading or write a transition between the two headings, for example: DESIGN AND METHODS This study is part of a mega … This section describes this study's objectives, participants and setting … Objectives Text … Participants and setting Text … When your analysis is in paragraphs, then edit and complement the information. The process table could be reformatted like this: Analysis occurred in these stages and yielded these results: (i) Watching and listening to videos of patients' morning wake-up routines, which gave us the big picture-an overview of patients' capabilities; (ii) transcribing the videos, which documented patients' capabilities in files and on paper; (iii) searching for frequently occurring words and phrases, which led to lists of words and phrases ready for categorization; and (iv) categorizing capabilities, which resulted in identification of frequently occurring categories of capabilities. Or like this: The methods described in this article (i) save development/writing time; (ii) reduce revision time (e.g., when dealing with reviewer/referee comments); (iii) cut translating and editing costs; (iv) facilitate development of clear, concise, consistent information; (v) enable replication of your study; and (vi) increase your chances of acceptance. Judy Petersen, Ph.D. is a freelance writer, editor, indexer, translator, trainer, and project manager. She owns and operates American Writing & Editing AB in Sweden (http://www.americanwitingandediting.se/). Contact Judy at judy.petersen@mailbox.swipnet.se

Clustering with partial information

The Correlation Clustering problem, also known as the Cluster Editing problem, seeks to edit a given graph by adding and deleting edges to obtain a collection of vertex-disjoint cliques, such that the editing cost is minimized. The Edge Clique Partitioning problem seeks to partition the edges of a given graph into edge-disjoint cliques, such that the number of cliques is minimized. Both problems are known to be NP-hard, and they have been previously studied with respect to approximation and fixed-parameter tractability. In this paper we study these two problems in a more general setting that we term fuzzy graphs, where the input graphs may have missing information, meaning that whether or not there is an edge between some pairs of vertices of the input graph can be undecided. For fuzzy graphs the Correlation Clustering and Edge Clique Partitioning problems have previously been studied only with respect to approximation. Here we give parameterized algorithms based on kernelization for both problems. We prove that the Correlation Clustering problem is fixed-parameter tractable on fuzzy graphs when parameterized by ( k , r ) , where k is the editing cost and r is the minimum number of vertices required to cover the undecided edges. In particular we show that it has a polynomial-time reduction to a problem kernel on O ( k 2 + r ) vertices. We provide an analogous result for the Edge Clique Partitioning problem on fuzzy graphs. Using ( k , r ) as parameters, where k bounds the size of the partition, and r is the minimum number of vertices required to cover the undecided edges, we describe a polynomial-time kernelization to a problem kernel on O ( k 4 ⋅ 3 r ) vertices. This implies fixed-parameter tractability for this parameterization. Furthermore we also show that parameterizing only by the number of cliques k , is not enough to obtain fixed-parameter tractability. The problem remains, in fact, NP-hard for each fixed k > 2 .

TER-Plus: paraphrase, semantic, and alignment enhancements to Translation Edit Rate

This paper describes a new evaluation metric, TER-Plus (TERp) for automatic evaluation of machine translation (MT). TERp is an extension of Translation Edit Rate (TER). It builds on the success of TER as an evaluation metric and alignment tool and addresses several of its weaknesses through the use of paraphrases, stemming, synonyms, as well as edit costs that can be automatically optimized to correlate better with various types of human judgments. We present a correlation study comparing TERp to BLEU, METEOR and TER, and illustrate that TERp can better evaluate translation adequacy.

La Revista Médica de Chile en el año 2009

During the first semester of 2009 Revista Médica de Chile has received an increasing number of manuscripts. Close to 30% were rejected while most other are in the process of being improved by the authors after receiving criticisms by external peer reviewers and the editors. The time lag between acceptance and publication of manuscripts is on an average six months. During 2008, 10% of articles published were submitted by authors from countries other than Chile and most of them were printed in English. Impact factor and other indexes provided by the ISI Web of Knowledge showed a promising improvement in 2008. The International Advisory Committee and the National Editorial Committee were renewed, a new Section on Laboratory Medicine was incorporated and several minor changes were done in design and format, in the title page and the issues' content. The main problems to be faced relate to the increasing cost of editing and printing, with a reduction in commercial advertising historically contributed by the pharmaceutical industry. Another major concern is to stimulate governmental agencies, scientific societies and universities to establish a national independent registry of clinical trials, that should become a mandatory requisite for every manuscript submitted to Chilean medical journals, reporting clinical trials performed in the country; foreign manuscripts should document the satisfaction of an identical requisite in their original source.

Revista Médica de Chile in the year 2009

During the first semester of 2009 Revista Médica de Chile has received an increasing number of manuscripts. Close to 30% were rejected while most other are in the process of being improved by the authors after receiving criticisms by external peer reviewers and the editors. The time lag between acceptance and publication of manuscripts is on an average six months. During 2008, 10% of articles published were submitted by authors from countries other than Chile and most of them were printed in English. Impact factor and other indexes provided by the ISI Web of Knowledge showed a promising improvement in 2008. The International Advisory Committee and the National Editorial Committee were renewed, a new Section on Laboratory Medicine was incorporated and several minor changes were done in design and format, in the title page and the issues' content. The main problems to be faced relate to the increasing cost of editing and printing, with a reduction in commercial advertising historically contributed by the pharmaceutical industry. Another major concern is to stimulate governmental agencies, scientific societies and universities to establish a national independent registry of clinical trials, that should become a mandatory requisite for every manuscript submitted to Chilean medical journals, reporting clinical trials performed in the country; foreign manuscripts should document the satisfaction of an identical requisite in their original source.

Performance-driven circuit and layout co-optimization for deep-submicron analog circuits

The deep sub-micron (DSM) process nodes are increasingly marred by layout-dependent effects. The principal reason preventing layout synthesis during circuit design is the cost of edition, verification and extraction of the intermediate solutions repeatedly. This paper proposes a circuit and layout co-optimization scheme through a novel parasitic model-building scheme that exchanges information between the two flows. A placement-based parasitic estimation method to provide parasitic estimations to schematic optimization tools while retaining their efficiency. Extracted parasitics and simulated performance data are imparted into parasitic macro-devices and performance sensitivities. As proved by experimental results, the flexibility of the parasitic models bridges the efficiency and accuracy void between schematic and physical design optimization to ensure rapid DSM design closure.

Going weighted: Parameterized algorithms for cluster editing

The goal of the Cluster Editing problem is to make the fewest changes to the edge set of an input graph such that the resulting graph is a disjoint union of cliques. This problem is NP-complete but recently, several parameterized algorithms have been proposed. In this paper, we present a number of surprisingly simple search tree algorithms for Weighted Cluster Editing assuming that edge insertion and deletion costs are positive integers. We show that the smallest search tree has size O ( 1.8 2 k ) for edit cost k , resulting in the currently fastest parameterized algorithm, both for this problem and its unweighted counterpart. We have implemented and compared our algorithms, and achieved promising results. 1 1 This is an extended version of two articles published in: Proc. of the 6th Asia Pacific Bioinformatics Conference, APBC 2008, in: Series on Advances in Bioinformatics and Computational Biology, vol. 5, Imperial College Press, pp. 211–220; and in: Proc. of the 2nd Conference on Combinatorial Optimization and Applications, COCOA 2008, in: LNCS, vol. 5038, Springer, pp. 289–302.