2164726
A New Planarity Test
Abstract Given an undirected graph, the planarity testing problem is to determine whether the graph can be drawn in a plane without any crossing edges. Linear time planarity testing algorithms have previously been designed by Hopcroft and Tarjan, and by Booth and Lueker. However, their approaches are quite involved. Several other approaches have also been developed for simplifying the planarity test. In this paper, we developed a very simple linear time testing algorithm based only on a depth-first search tree. When the given graph is not planar, our algorithm immediately produces explicit Kuratowski's subgraphs. A new data structure, PC -trees, is introduced, which can be viewed as abstract subembeddings of actual planar embeddings. A graph-reduction technique is adopted so that the embeddings for the planar biconnected components constructed at each iteration never have to be changed. The recognition and embedding are actually done simultaneously in our algorithm (Booth and Lueker, 1976). The implementation of our algorithm is quite straightforward.
6232755
Algorithms for minimum covering by cliques and maximum clique in claw-free perfect graphs
An algorithm is given for determining a minimum cardinality clique cover ongraphs that do not contain claws, odd holes or odd anti-holes. These graphs are also shown to be perfect so that we obtain a new proof of the strong perfect graph theorem for claw-free graphs. A by-product of our analysis is an algorithm for determining a maximum cardinality clique on claw-free perfect graphs.
17795095
A Simple Test for the Consecutive Ones Property
A (0,1)-matrix satisfies the consecutive ones property if there exists a column permutation such that the one's in each row of the resulting matrix are consecutive. Booth and Lueker [1976] designed a linear time testing algorithm for this property based on a data structure called “PQ-trees”. This procedure is very complicated and the linear time amortized analysis is also rather involved. We develop an off-line testing algorithm for the consecutive ones property without using PQ-trees. Our approach is based on a decomposition technique which separates the rows into “prime” subsets which admit unique column orderings that realize the consecutive ones property. The success of this approach is based on finding a good “row ordering” to be tested iteratively.
1251407
Reference metadata extraction using a hierarchical knowledge representation framework
The integration of bibliographical information on scholarly publications available on the Internet is an important task in the academic community. Accurate reference metadata extraction from such publications is essential for the integration of metadata from heterogeneous reference sources. In this paper, we propose a hierarchical template-based reference metadata extraction method for scholarly publications. We adopt a hierarchical knowledge representation framework called INFOMAP, which automatically extracts metadata. The experimental results show that, by using INFOMAP, we can extract author, title, journal, volume, number (issue), year, and page information from different kinds of reference styles with a high degree of precision. The overall average accuracy is 92.39% for the six major reference styles compared in this study.
341424
Domain Event Extraction and Representation with Domain Ontology
With domain ontology, a meaningful index of document indexing, such as the domain events structure in this paper, can be defined. Since the construction of domain ontology is costly, an automatic domain ontology acquisition is preferred. We find that named entity can be a clue of domain event acquisition from the training corpus. Therefore , we add the named entity recognition module into the automatic domain ontology acquisition process. Thus, a subject-verb-object-modifier (SVOM) indexing can be constructed. Our experimental results demonstrate that the automatic event extraction and ontology acquisition can be good resources for text categorization and further information processing.
6185076
Text categorization using automatically acquired domain ontology
In this paper, we describe ontology-based text categorization in which the domain ontologies are automatically acquired through morphological rules and statistical methods. The ontology-based approach is a promising way for general information retrieval applications such as knowledge management or knowledge discovery. As a way to evaluate the quality of domain ontologies, we test our method through several experiments. Automatically acquired domain ontologies, with or without manual editing, have been used for text categorization. The results are quite satisfactory. Furthermore, we have developed an automatic method to evaluate the quality of our domain ontology.
15536153
Applying Cilk in Provably Efficient Task Scheduling
We consider the application of Cilk, a C-based runtime system for multithreaded parallel programming, in scheduling static task graphs. We assume no pre-emption of task execution and no prior knowledge of the task execution times. Given a task graph G, the output of the scheduling algorithm is a Cilk program which, when executed, will initiate the tasks in a manner consistent with the precedence requirement of G. We rst report a restriction arising from the computational model of Cilk in task scheduling, in the sense that optimal scheduling may not be achievable with Cilk for certain task graphs. Luckily the restriction does not fundamentally hinder the practical application of the Cilk tool, as we next show that it is possible to quickly produce a reasonably good quality schedule in the sense of expected execution time. Given a task graph, our algorithm partitions the task nodes into subsets called bundles. Each bundle is mapped into a Cilk procedure. The output program then consists of a series of such Cilk procedures. By using Tarjan's disjoint-set algorithm for handling the bundles, we demonstrate that the parallel schedule can be derived in O(n + e) time for all practical purposes, whereand e denote the number of nodes and edges in the task graph. We further show that, with P processors, the expected completion time for the scheduled tasks achieves a near-optimum of T P T 1 = P + 1:5T 1 , where T 1 denotes the work, i.e., the sequential execution time of all tasks, and T 1 denotes the critical path, i.e., the total execution time of all tasks lying on the longest dependency path. Our work represents a serious attempt to use Cilk to handle complicated types of concurrency.
5367915
A Maximum Entropy Approach to Biomedical Named Entity Recognition
Machine learning approaches are frequently used to solve name entity (NE) recognition (NER). In this paper we propose a hybrid method that uses maximum entropy (ME) as the underlying machine learning method incorporated with dictionary-based and rule-based methods for post-processing. Simply using ME for NER, inaccurate boundary detection of NEs and misclassification may occur. Some NEs are partially recognized by ME. In the post-processing stage, we use dictionary-based and rule-based methods to extend boundary of partially recognized NEs and to adjust classification. We use GENIA corpus 3.01 to conduct 10-fold cross-verification experiments. To evaluate the performance, we consider the longest NE annotations. We evaluate our approach using standard precision (P), recall (R), and F-score, where F-score is defined as 2PR/(P+R). The precision, recall and F-score ([P, R, F]) of our ME module for overall 23 categories is [0.512, 0.538, 0.525], and after the post-processing the performance becomes [0.729, 0.711, 0.72] for [P, R, F]. For protein, DNA and RNA classes, our method achieves [P, R, F] of [0.77, 0.80, 0.785], [0.653, 0.748, 0.7], and [0.716, 0.788, 0.752], respectively. The post-processing stage significantly improves the performance of our ME-based NER module.