The Experts below are selected from a list of 152580 Experts worldwide ranked by ideXlab platform
Xiaoqing Liu - One of the best experts on this subject based on the ideXlab platform.
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web service discovery based on goal oriented query expansion
Journal of Systems and Software, 2018Co-Authors: Neng Zhang, Jian Wang, Xiaoqing LiuAbstract:Abstract With the broad adoption of service-oriented architecture, many software systems have been developed by composing loosely-coupled Web services. Service discovery, a critical step of building service-based systems (SBSs), aims to find a set of candidate services for each functional task to be performed by an SBS. The keyword-based Search Technology adopted by existing service registries is insufficient to retrieve semantically similar services for queries. Although many semantics-aware service discovery approaches have been proposed, they are hard to apply in practice due to the difficulties in ontology construction and semantic annotation. This paper aims to help service requesters (e.g., SBS designers) obtain relevant services accurately with a keyword query by exploiting domain knowledge about service functionalities (i.e., service goals) mined from textual descriptions of services. We firstly extract service goals from services’ textual descriptions using an NLP-based method and cluster service goals by measuring their semantic similarities. A query expansion approach is then proposed to help service requesters refine initial queries by recommending similar service goals. Finally, we develop a hybrid service discovery approach by integrating goal-based matching with two practical approaches: keyword-based and topic model-based. Experiments conducted on a real-world dataset show the effectiveness of our approach.
R Weeks - One of the best experts on this subject based on the ideXlab platform.
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quizrdf Search Technology for the semantic web
Hawaii International Conference on System Sciences, 2004Co-Authors: John Davies, R WeeksAbstract:An information-seeking system is described which combines traditional keyword querying of WWW resources with the ability to browse and query against RDF annotations of those resources. RDF(S) and RDF are used to specify and populate an ontology and the resultant RDF annotations are then indexed along with the full text of the annotated resources. The resultant index allows both keyword querying against the full text of the document and the literal values occurring in the RDF annotations, along with the ability to browse and query the ontology. We motivate our approach as a key enabler for fully exploiting the semantic Web in the area of knowledge management and argue that the ability to combine Searching and browsing behaviours more fully supports a typical information-seeking task. The approach is characterised as "low threshold, high ceiling" in the sense that where RDF annotations exist they are exploited for an improved information-seeking experience but where they do not yet exist, a Search capability is still available.
Du Hua - One of the best experts on this subject based on the ideXlab platform.
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design and implement of vertical Search engine
Information Sciences, 2011Co-Authors: Du HuaAbstract:Faced with increasingly professional and personalized needs of information retrieval,the problem for general Search engine is exposed.It is more and more attention for vertical Search Technology as a major direction of Search engine development.To gives the general structure of a vertical Search engine,based on it,the key technologies involved are analyzed in detail: Web crawling,Chinese word segmentation,text classification and so on.And segmentation and classification algorithms add to the Nutch,realizing a prototype system.Experiments show that the degree of the system subject is to 94%.
An Chen - One of the best experts on this subject based on the ideXlab platform.
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grid Search parametric optimization for ft nir quantitative analysis of solid soluble content in strawberry samples
Vibrational Spectroscopy, 2018Co-Authors: Huazhou Chen, Zhenyao Liu, Ken Cai, An ChenAbstract:Abstract Grid Search Technology is proposed to choose the influencing parameters for interval partial least squares (iPLS) and moving window partial least squares (MWPLS) models in the Fourier transform near infrared (FT-NIR) spectrometric quantitative determination of solid soluble content (SSC) in strawberry samples. The objective of grid Search is to find out a robust way to ensure that the selected parameters of iPLS and MWPLS would output the informative wavebands leading to improved modeling results. For the improvement of model accuracy, the grid Search technique is designed for locating the informative wavebands via influential algorithmic parameters on FT-NIR regions corresponding to different spectral responses of molecule vibration. The commonly used iPLS and MWPLS algorithms are modified in cooperation with the grid Search technique, to identify the informative wavebands for the improvement of the model prediction performances. A further integration of the wavebands from different regions could obtain some more accurate models based on the calibrating-validating-testing (CVT) sample division framework. The optimized parameters have the potential to be applied to the development of online and realtime measurement for fruit industry.
Le-khac Nhien-an - One of the best experts on this subject based on the ideXlab platform.
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Shining a light on Spotlight: Leveraging Apple's desktop Search utility to recover deleted file metadata on macOS
'Elsevier BV', 2019Co-Authors: Atwal, Tajvinder Singh, Scanlon Mark, Le-khac Nhien-anAbstract:Spotlight is a proprietary desktop Search Technology released by Apple in 2004 for its Macintosh operating system Mac OS X 10.4 (Tiger) and remains as a feature in current releases of macOS. Spotlight allows users to Search for files or information by querying databases populated with filesystem attributes, metadata, and indexed textual content. Existing forensic reSearch into Spotlight has provided an understanding of the metadata attributes stored within the metadata store database. Current approaches in the literature have also enabled the extraction of metadata records for extant files, but not for deleted files. The objective of this paper is to reSearch the persistence of records for deleted files within Spotlight's metadata store, identify if deleted database pages are recoverable from unallocated space on the volume, and to present a strategy for the processing of discovered records. In this paper, the structure of the metadata store database is outlined, and experimentation reveals that records persist for a period of time within the database but once deleted, are no longer recoverable. The experimentation also demonstrates that deleted pages from the database (containing metadata records) are recoverable from unused space on the filesystem.Comment: Digital Investigation (2019
