3138071
Statistical relationship determination in automatic thesaurus construction
Statistical relationship determination among terms is one of the key issues in automatic thesaurus construction. We systematically analyze existing relevant approaches based on their underlying probabilistic assumptions, and propose a combined approach that overcomes their limitations.
33456865
Enterprise Information Integration - A Semantic Approach
Nowadays, we witness the advent of a new era in information technology as an enabler for an often proclaimed “knowledged society”. Many academicians – computer scientists, computational linguists and others – but also researchers in corporate settings investigate the use of “knowledge” as a means for intelligent information access in enterprises. Ontologies are commonly considered a formal means for modelling and instantiating conceptual structures upon which implicit knowledge can be inferred. In an industrial context, however, domain-specific conceptual information is only one corporate information resource. Relevant business information comprises facts on goods, projects, experts, customers, competitors and many other information bits as they are stored in enterprise information systems. A great wish of many executives is, however, to gain an integrated view on these assets and their relationships, thus deriving new insights relevant for their business. To achieve this goal, ontologies can help with respect to semantic data integration. A problem is, however, that the construction and maintenance of ontologies is expensive. Another problem is that the business data are usually stored redundantly in different heterogeneous data repositories and the connectivity – a prerequisite for intelligence – is not explicit. The approach discussed in the remainder will show how a mix of information extraction and classification methods can be used to automatically set-up and update a network of business objects serving as a corporate memory index. The latter represents a rich semantic access structure for filtering and individualizing the retrieval of relevant business information.
207154117
The Layer-Seeds Term Clustering Method: Enabling Proactive Situation-Aware Product Recommendations in E-Commerce Dialogues
In e-commerce it is often crucial to provide customers a large choice of relevant offers. Users, however, seldom provides complete and comprehensive descriptions of their desires, therefore user interfaces are needed that can generate automatically expanded queries to the product database and proactively enrich the ongoing dialogue with recommendations of suitable products. Automatic query expansion is mostly based on thesaurus and/or user profiles. In e-commerce applications, specific thesauri reflecting the webstore's product categories are desirable. This work describes a method for the automatic construction of a thesaurus based on existing categories of documents. A clustering algorithm, the “Layer-Seeds method'', is introduced, which facilitates the automatic generation of thesaurus reflecting the specific vocabulary occurring in a given collection of documents. The clustering works on terms extracted from the documents in a certain category and organizes them in a tree-like hierarchical structure—a thesaurus. The thesaurus is then employed for automatic query expansion in an e-commerce application in order to obtain better results for product searching. Experiments yield evidence that a significant increase of user satisfaction is achieved.
26888449
Language Modeling for Effective Construction of Domain Specific Thesauri
In this paper we present an approach for effective construction of domain specific thesauri. We assume that the collection is partitioned into document categories. By taking advantage of these pre-defined categories, we are able to conceptualize a new topical language model to weight term topicality more accurately. With the help of information theory, interesting relationships among thesaurus elements are discovered deductively. Based on the “Layer-Seeds” clustering algorithm, topical terms from documents in a certain category will be organized according to their relationships in a tree-like hierarchical structure — a thesaurus. Experimental results show that the thesaurus contains satisfactory structures, although it differs to some extent from a manually created thesaurus. A first evaluation of the thesaurus in a query expansion task yields evidence that an increase of recall can be achieved without loss of precision.
30915392
An HCI method to improve the human performance reduced by local-lag mechanism
Local-lag mechanism can maintain consistency for replicated continuous applications, but with a tradeoff of adding delay to local operations. To relieve the negative effects of the delay, this paper proposes an HCI method named echo. With the help of the echo method users can immediately perceive the results of their operations and how large the lag is. In order to evaluate the proposed method, a desktop collaborative virtual environment (CVE) system and a virtual object control task were employed to study the effects of the echo method on human performance (including task completion time, error count, and interaction quality). Experimental results indicate that when the lag exceeds 100ms the echo method can improve human performance with the effects becoming more evident when a larger lag is used.
207717559
Associative Clustering for Clusters of Arbitrary Distribution Shapes
A novel neural network, named Associative Clustering Neural Network (ACNN), is developed for clustering data whose underlying distribution shapes are arbitrary. ACNN is a dynamic model that collectively measures and updates the similarity of any two patterns through the interaction of a group of patterns. Such a new measure of similarity helps to achieve more robust clustering performance than using the existing measures that are staticly and individually based on the distances among the isolated pairwise data. The efficience of ACNN has been verified through the performance study.
31293594
Integrating mRNA Decay Information into Co-Regulation Study
Absolute or relative transcript amounts measured through high-throughput technologies (e.g., microarrays) are now commonly used in bioinformatics analysis, such as gene clustering and DNA binding motif finding. However, transcription rates that represent mRNA synthesis may be more relevant in these analyses. Because transcription rates are not equivalent to transcript amounts unless the mRNA degradation rates as well as other factors that affect transcript amount are identical across different genes, the use of transcription rates in bioinformatics analysis may lead to a better description of the relationships among genes and better identification of genomic signals. In this article, we propose to use experimentally measured mRNA decay rates and mRNA transcript amounts to jointly infer transcription rates, and then use the inferred transcription rates in downstream analyses. For gene expression similarity analysis, we find that there tends to be higher correlations among co-regulated genes when transcription-rate-based correlations are used compared to those based on transcript amounts. In the context of identifying DNA binding motifs, using inferred transcription rates leads to more significant findings than those based on transcript amounts. These analyses suggest that the incorporation of mRNA decay rates and the use of the inferred transcription rates can facilitate the study of gene regulations and the reconstruction of transcriptional regulatory networks.
42859429
Hardware verification using symbolic state transition graphs
A new approach for hardware verification using symbolic state transition graphs (implemented in BDDs) is presented. We propose a novel idea, a symbolic state transition graph (STG), which can represent finite state machines FSM in terms of the relations between symbolic input variables, state variables, and output results, rather than the exact input-output bit patterns. Compared to conventional STG methods, the symbolic STG is more concise, higher-level, has fewer states and is easier to specify. Based on the transition relation method and an event-driven scheduling technique to compute the symbolic states, we propose two algorithms to verify the circuit implementation with respect to its symbolic STGs. The algorithms can be used to find out a necessary condition for the implementation to satisfy the specification, which can be used for the allocation of design errors.<<ETX>>
4775385
A fine-grained replacement strategy for XML query cache
Caching popular queries and reusing results of previously computed queries is one important query optimization technique, especially in modern distributed environments such as the WWW. Based on the recent proliferation of XML data and the emergence of the XQuery language, we are thus developing a query- based caching system for XQuery queries, called ACE-XQ. ACE-XQ applies innovative query containment and rewriting strategies to answer incoming user queries based on the cached XQueries, whenever possible, instead of accessing remote XML data sources.To manage the space of the cache, a straightforward application of traditional replacement strategies would correspond to removing a complete cached query and its derived XML document as a whole when space needs to be freed. This coarse granularity however does not match well with the typical access pattern of web searches where new queries often partially overlap with cached queries.In this paper, we propose a novel replacement strategy appropriate for such query-based XML caching systems. In particular, we collect user access statistics at the granularity of the XML path structure instead of the complete XML query regions. We then apply a more fine-grained replacement strategy that purges XML fragments off a cached region instead of the whole XML document and accordingly adjusts the query descriptor. This may better capture the user access patterns since more frequently used XML document fragments are likely to remain in the cache while other less beneficial parts are purged. This approach has been implemented in our ACE-XQ System. Preliminary experiment results illustrate the performance improvement achievable by our fine-grained replacement strategy over the one which replaces a whole XML view at a time when the cache size is relatively large.