14566859
Various criteria in the evaluation of biomedical named entity recognition
BackgroundText mining in the biomedical domain is receiving increasing attention. A key component of this process is named entity recognition (NER). Generally speaking, two annotated corpora, GENIA and GENETAG, are most frequently used for training and testing biomedical named entity recognition (Bio-NER) systems. JNLPBA and BioCreAtIvE are two major Bio-NER tasks using these corpora. Both tasks take different approaches to corpus annotation and use different matching criteria to evaluate system performance. This paper details these differences and describes alternative criteria. We then examine the impact of different criteria and annotation schemes on system performance by retesting systems participated in the above two tasks.ResultsTo analyze the difference between JNLPBA's and BioCreAtIvE's evaluation, we conduct Experiment 1 to evaluate the top four JNLPBA systems using BioCreAtIvE's classification scheme. We then compare them with the top four BioCreAtIvE systems. Among them, three systems participated in both tasks, and each has an F-score lower on JNLPBA than on BioCreAtIvE. In Experiment 2, we apply hypothesis testing and correlation coefficient to find alternatives to BioCreAtIvE's evaluation scheme. It shows that right-match and left-match criteria have no significant difference with BioCreAtIvE. In Experiment 3, we propose a customized relaxed-match criterion that uses right match and merges JNLPBA's five NE classes into two, which achieves an F-score of 81.5%. In Experiment 4, we evaluate a range of five matching criteria from loose to strict on the top JNLPBA system and examine the percentage of false negatives. Our experiment gives the relative change in precision, recall and F-score as matching criteria are relaxed.ConclusionIn many applications, biomedical NEs could have several acceptable tags, which might just differ in their left or right boundaries. However, most corpora annotate only one of them. In our experiment, we found that right match and left match can be appropriate alternatives to JNLPBA and BioCreAtIvE's matching criteria. In addition, our relaxed-match criterion demonstrates that users can define their own relaxed criteria that correspond more realistically to their application requirements.
17603178
A Linear Time Algorithm for Finding a Maximal Planar Subgraph Based on PC-Trees
In Shih & Hsu, a planarity test was introduced utilizing a data structure called PC-trees, generalized from PQ-trees. They illustrated that a PC-tree is more natural in representing planar graphs. Their algorithm starts by constructing a depth-first-search tree and adds all back edges to a vertex one by one. An important feature in the S&H algorithm is that, at each iteration, at most two terminal nodes need to be computed and the unique tree path between these two nodes provides essentially the boundary path of the newly formed biconnected component. 
 
In this paper we modify their PC-tree algorithm and introduce the deferred planarity test (DPT), which has the added benefit of finding a maximal planar subgraph (MPS) in linear time when the given graph is not planar. DPT is an incremental algorithm, which only computes a partial terminal path at each iteration. DPT continually deletes back edges that could create a violation to the formation of those partial terminal paths so that, at the end, the subgraph constructed is guaranteed to be planar. 
 
The key to the efficiency of the S&H and the DPT algorithms lies in their management on the creation and destruction of biconnected components in which the PC-tree plays a major role. Previously, there have been reports that the MPS problem can be solved in linear time. However, there was no concrete data structure realizing them.
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.
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.
5724385
An iterative relaxation technique for the NMR backbone assignment problem
NMR spectroscopy is one of the popular experiments to determine protein structures. An important stage of protein structure determination by using NMR is protein backbone resonance assignment (or backbone assignment for short). Due to the messiness and disorder of NMR spectral data, backbone assignment is usually a tedious and time-consuming manual work. This raises a great interest in developing an efficient and automatic method to perform backbone assignment. An iterative algorithm is proposed that is equipped with two operations: grouping and linking. Grouping is responsible for peak picking and part of connectivity determination. Ideally, those peaks with the same H/sup N/ and N chemical shifts can be grouped together; peaks belonging to the same group can be used to determine the order of two consecutive spin systems. However, in real situation, grouping is a difficult task due to false positives and false negatives. We sometimes add hypothetic peaks to tackle false negatives and use linking operation to remove false positives. Linking is responsible for part of connectivity determination and backbone assignment. Given a protein sequence and partial connectivity information, we try to link connected spin systems as much as possible. False positive spin systems may create conflicts in the linking stage. To find a good assignment on a noisy dataset, the backbone assignment problem is modeled as a maximum independent set problem. Although the problem is NP-complete, there are heuristic methods that obtain pretty good results.
16227528
Fast image retrieval using color-spatial information
Abstract. In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for “optimal'' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism.
931369
Improving cache performance with balanced tag and data paths
There are two concurrent paths in a typical cache access --- one through the data array and the other through the tag array. The path through the data array drives the selected set out of the array. The path through the tag array determines cache hit/miss and, for set-associative caches, selects the appropriate line from within the selected set. In both direct-mapped and set-associative caches, the path through the tag array is significantly longer than that through the data array. In this paper, we propose a path balancing technique help match the delays of the tag and data paths. The basic idea behind this technique is to employ a separate subset of the tag array to decouple the one-to-one relationship between address tags and cache lines so as to achieve a design that provides higher performance. Performance evaluation using both TPC-C and SPEC92 benchmarks shows that this path balancing technique offers impressive improvements in overall system performance over conventional cache designs. For TPC-C, improvements in the range of 6% to 28% are possible.
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.
308038
Projecting the performance of decision support workloads on systems with smart storage (SmartSTOR)
Recent developments in both hardware and software have made it worthwhile to consider embedding intelligence in storage to handle general-purpose processing that can be off-loaded from the hosts. In particular, low-cost processing power is now widely available and software can be made robust, secure and mobile. In this paper, we propose a general smart storage (SmartSTOR) architecture in which a processing unit that is coupled to one or more disks can be used to perform such off-loaded processing. A major part of the paper is devoted to understanding the performance potential of the SmartSTOR architecture for decision support workloads. Our analysis suggests that there is a definite performance advantage in using fewer but more powerful processors, a result that bolsters the case for sharing a powerful processor among multiple disks. As for software architecture, we find that the off-loading of database operations that involve only a single relation is not very promising. In order to achieve significant speed-up, we have to consider the off-loading of multiple-relation operations. In general, if embedding intelligence in storage is an inevitable architectural trend, we have to focus on developing parallel software systems that can effectively take advantage of the large number of processing units that will be in the system.
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.