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.
7952210
Semi-automatic transformation from formal specifications to programs
As model-based formal methods (e.g. VDM, Z) are becoming popular for the development of safety-critical and complex systems in industry, automatic transformation from formal specifications to programs is an ideal and efficient approach to software production. However, it is impossible in general for this transformation to be fully automatic, because the language of first order logic used for specification is not decidable. This paper uses VDM (Vienna Development Method) as an example to investigate this difficulty, and proposes an approach to address the problem. Rules for automatically transforming abstract level VDM specifications are described and further transformation at a detailed level is discussed. Finally, further work towards the construction of a rule-based software system to support the transformation from VDM specifications to programs in general is addressed.
9811887
A formal operational semantics for SOFL
SOFL (Structured-Object-Based-Formal Language) is a formal language and method for practical systems development. As a language, it integrates data flow diagrams, VDM-SL, and Petri nets to provide a graphical and textual formal notation for specification construction. Previous publications introducing SOFL are based on its informal semantics. We provide a formal operational semantics which gives a firm foundation for consistent understanding and application of SOFL in practical systems development. Development of the semantics, and application of SOFL to practical systems, have led to some changes in the original definitions. This formal semantics will serve as a firm foundation for building an effective support environment for SOFL.
1673600
Inferring Data Transformation Rules to Integrate Semantic Web Services
OWL-S allows selecting, composing and invoking Web Services at different levels of abstraction: selection uses high level abstract descriptions, invocation uses low level grounding ones, while composition needs to consider both high and low level descriptions. In our setting, two Web Services are to be composed so that output from the upstream one is used to create input for the downstream one. These Web Services may have different data models but are related to each other through high and low level descriptions. 
 
Correspondences must be found between components of the upstream data type and the downstream ones. Low level data transformation functions may be required (e.g. unit conversions, data type conversions). The components may be arranged in different XML tree structures. Thus, multiple data transformations are necessary: reshaping the message tree, matching leaves by corresponding types, translating through ontologies, and calling conversion functions. Our prototype compiles these transformations into a set of data transformation rules, using our tableau-based ALC Description Logic reasoner to reason over the given OWL-S and WSDL descriptions, as well as the related ontologies. A resolution-based inference mechanism for running these rules is embedded in an inference queue that conducts data from the upstream to the downstream service, running the rules to perform the data transformation in the process.
30881235
Criteria for generating specification-based tests
This paper presents general criteria for generating test inputs from state-based specifications. Software testing can only be formalized and quantified when a solid basis for test generation can be defined. Formal specifications of complex systems represent a significant opportunity for testing because they precisely describe what functions the software is supposed to provide in a form that can easily be manipulated. These techniques provide coverage criteria that are based on the specifications, and are made up of several parts, including test prefixes that contain inputs necessary to put the software into the appropriate state for the test values. The test generation process includes several steps for transforming specifications to tests. Empirical results from a comparative case study application of these criteria are presented.
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.