14446563
Vague Content and Structure (VCAS) Retrieval for Document-centric XML Collections
document-centric XML collections with structure conditions improves retrieval precisions. The structures of such XML collections, however, are often too complex for users to fully grasp. Thus, for queries regarding such collections, it is more appropriate to retrieve answers that approximately match the structure and content conditions in these queries, a process also known as vague content and structure (VCAS) retrieval. Most existing XML engines, however, only support content-only (CO) retrieval and/or strict content and structure (SCAS) retrieval. To remedy these shortcomings, we propose an approach for VCAS retrieval using existing XML engines. Our approach first decomposes a VCAS query into a SCAS sub-query and a CO sub- query, then uses existing XML engines to retrieve SCAS results and CO results for the decomposed sub-queries, and finally combines results from both retrievals to produce approximate results for the original query. Further, to improve retrieval precision, we propose two similarity metrics to adjust the scores of CO retrieval results by their relevancies to the path condition for the original query target. We evaluate our VCAS retrieval approach through extensive experiments with the INEX 04 XML collection and VCAS query sets. The experimental results demonstrate the effectiveness of our VCAS retrieval approach.
2799415
Using a compact tree to index and query XML data
Indexing XML is crucial for efficient XML query processing. We propose a compact tree (Ctree) for XML indexing, which provides not only concise path summaries at group level but also detailed child-parent relationships at element level. Based on Ctree, we are able to measure how well XML data is structured. We also propose a three-step query processing method. Its efficiency is achieved by: (1) summarizing large XML data structures into a condensed Ctree; (2) pruning irrelevant groups to significantly reduce the search space; (3) eliminating join operations between the matches for value predicates and those for structure constraints and (4) using Ctree properties such as regular groups to reduce query processing time. Our experiments reveal that Ctree is an effective data structure for managing XML data.
5842197
Configurable indexing and ranking for XML information retrieval
Indexing and ranking are two key factors for efficient and effective XML information retrieval. Inappropriate indexing may result in false negatives and false positives, and improper ranking may lead to low precisions. In this paper, we propose a configurable XML information retrieval system, in which users can configure appropriate index types for XML tags and text contents. Based on users' index configurations, the system transforms XML structures into a compact tree representation, Ctree, and indexes XML text contents. To support XML ranking, we propose the concepts of "weighted term frequency" and "inverted element frequency," where the weight of a term depends on its frequency and location within an XML element as well as its popularity among similar elements in an XML dataset. We evaluate the effectiveness of our system through extensive experiments on the INEX 03 dataset and 30 content and structure (CAS) topics. The experimental results reveal that our system has significantly high precision at low recall regions and achieves the highest average precision (0.3309) as compared with 38 official INEX 03 submissions using the strict evaluation metric.
6631927
Ctree: a compact tree for indexing XML data
In this paper, we propose a novel compact tree (Ctree) for XML indexing, which provides not only concise path summaries at the group level but also detailed child-parent links at the element level. Group level mapping allows efficient pruning of a large search space while element level mapping provides fast access to the parent of an element. Due to the tree nature of XML data and queries, such fast child-to-parent access is essential for efficient XML query processing. Using group-based element reference, Ctree enables the clustering of inverted lists according to groups, which provides efficient join between inverted lists and structural index group extents. Our experiments reveal that Ctree is efficient for processing both single-path and branching queries with various value predicates.
14652555
Adding multi-class routing into the DiffServ architecture
To alleviate the problem of high priority traffic hogging of all the available network capacity and to optimize the network traffic in the DiffServ network, we introduce the multi-class routing (MCR) scheme into the DiffServ architecture. The MCR scheme that builds multiple routing tables in the DiffServ routers forms the MCR DiffServ architecture. In this paper, the MCR DiffServ architecture focuses on the intra-DS domain. Different MCR approaches that include a static approach and dynamic approaches can be used for the MCR DiffServ system. We extend the OSPF protocol in order to build up more than one routing table in each MCR DiffServ system. According to the extensions to OSPF, we have implemented the static MCR approach for the MCR DiffServ system on the basis of the open source Zebra software.
1315911
An Object Semantic Model of SOFL
SOFL (Structured-Object-based-Formal Language) is recently proposed to combine the advantages of formal methods, structured methods and object-oriented methodology into one method for software development. SOFL integrates modeling techniques from VDM (for specifying system component state) and data flow diagrams with Petri nets (for specifying system behaviours and interaction). To support the standardisation and the tool support for SOFL, a formal semantics of the language is desirable. As SOFL is under further development, the semantic representation of current SOFL needs to be easily reused and extended. In this paper, an object-oriented approach is taken to specify the semantics of SOFL and this approach is proved to be effective in providing a modular and reusable semantic representation. Object modeling techniques, such as inheritance is used to illustrate the common and the differences between various SOFL graphical constructs; object containment is used to capture the acyclic structure of SOFL hierarchical module decomposition.
14203644
Word sense disambiguation in queries
This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense disambiguation. By comparing these pieces of information associated with the words which form a phrase, it may be possible to assign senses to these words. If the above disambiguation fails, then other query words, if exist, are used, by going through exactly the same process. If the sense of a query word cannot be determined in this manner, then a guess of the sense of the word is made, if the guess has at least 50% chance of being correct. If no sense of the word has 50% or higher chance of being used, then we apply a Web search to assist in the word sense disambiguation process. Experimental results show that our approach has 100% applicability and 90% accuracy on the most recent robust track of TREC collection of 250 queries. We combine this disambiguation algorithm to our retrieval system to examine the effect of word sense disambiguation in text retrieval. Experimental results show that the disambiguation algorithm together with other components of our retrieval system yield a result which is 13.7% above that produced by the same system but without the disambiguation, and 9.2% above that produced by using Lesk's algorithm. Our retrieval effectiveness is 7% better than the best reported result in the literature.
18135743
A clustering entropy-driven approach for exploring and exploiting noisy functions
Linear, Gaussian, fitness proportional, clustering, and Rosca entropies are succinct measures of diversity that have been applied to balance exploration and exploitation in evolutionary algorithms. In previous studies, an entropy-driven approach using linear entropy explicitly balances and/or searches optimal solutions for the selected unimodal and multimodal functions excluding noisy functions. This paper investigates the reasons for such an exception and introduces a clustering entropy-driven approach to solve the problem. Such an approach provides a coarse-grained diversity measure that filters the noise of functions, varies cluster size and categorizes individuals at the genotype level. The experimental results show that the clustering entropy-driven approach further improves the searching results of noisy functions by one more degree.
23663426
Evolution: a more practical approach than refinement for software development
Refinement of operations is well defined in terms of refinement rules and is considered as a reasonable discipline for software development. This paper, however, observes that refinement is not sufficient to serve this role for the entire software development process and then proposes evolution for substitution. We show that refinement is indeed a special case of evolution and evolution is transitive. A small case study is given to demonstrate that using evolution rather than refinement as the discipline for software development is a more practical approach. The idea presented in this paper may be controversial, but the author believes that this idea is more useful, practical, and instructive than refinement approach, and expects to inspire more discussions about this issue.