Web service searching

With the growing number of Web services, it is no longer adequate to locate a Web service by searching its name or browsing a UDDI directory. An efficient Web services discovery mechanism is necessary for locating and selecting the required Web services. Searching mechanism should be based on Web service description rather than on keywords. In this work, we introduce a Web service searching prototype that can locate Web services by comparing all available information encoded in Web service description, such as operation name, input and output types, the structure of the underlying XML schema, and the semantic of element names. Our approach combines information-retrieval techniques, weighted bipartite graph matching algorithm and tree-matching algorithm. Given a query, represented as set of keywords, Web service description, or operation description, an information retrieval technique is used to rank the candidate Web services based on their text-base similarity to the query. The ranked result can be further refined by computing their structure similarity. (Abstract shortened by UMI.) Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .J34. Source: Masters Abstracts International, Volume: 44-03, page: 1403. Thesis (M.Sc.)--University of Windsor (Canada), 2005

A Compressive Survey on New Technique Towards Successful Document Research Using Key Phrase Annotations Together with Querying Benefit

Generally it can be challenging to find out the particular pertinent data inside unstructured wording paperwork. This kind of information is still suffocated within unstructured wording and terminology. Annotations by means of Characteristic name-value frames tend to be more significant for retrieval of this sort of documents. This system proposes a novel, different, alternative approach for document retrieval which includes annotations identification. This system identifies the values of structured attributes by reading, analyzing and parsing the uploaded documents. This system proposes an approach for efficient document retrieval using effective methods. The main use of this system is that when users of author perform query based search, they could get minimum and distinct accurate results where it could be easy for retr ieval data from the database. By using these techniques two techniques, workload of system can reduce by large amount. And it also, given the fact the effic iency of searching annotation document will be faster because of using the query-based searching technique or content value searching

AKSES JENIS DOKUMEN PADA BASIS DATA TERPADU: SUATU TINJAUAN TERHADAP OPAC DI PDII-LIPI

Integrated data base is a data base records bibliographic data of several types of document like textbook, periodicals, proceedings, research report, thesis, and article. Purposes of this study were to investigate document type description and searching strategy in integrated data base of online public access catalogs (OPAC) in PDII-LIPI, and to know user opinion about that data base existence. It used observation and interviews to 100 data base users to collect data. Result of this study stated that document type description in OPAC was not indexed, so users couldn't do information searching of special type of document directly in the data base. There was only one method could be used to search information of special type of document. User could select it from some information records on the computer screen as the result of document title, author name or subject searching in the data base. This information access method was not efficient. So document type description and indexing was an important factor and should be done in information retrieval system using integrated data base. But respondent majority (84%) in PDII-LIPI stated that they liked using separated data base to search information of special type of document

Enhancing information retrieval in folksonomies using ontology of place constructed from Gazetteer information

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesFolksonomy (from folk and taxonomy) is an approach to user metadata creation where users describe information objects with a free-form list of keywords (‘tags’). Folksonomy has have proved to be a useful information retrieval tool that support the emergence of “collective intelligence” or “bottom-up” light weight semantics. Since there are no guiding rules or restrictions on the users, folksonomy has some drawbacks and problems as lack of hierarchy, synonym control, and semantic precision. This research aims at enhancing information retrieval in folksonomy, particularly that of location information, by establishing explicit relationships between place name tags. To accomplish this, an automated approach is developed. The approach starts by retrieving tags from Flickr. The tags are then filtered to identify those that represent place names. Next, the gazetteer service that is a knowledge organization system for spatial information is used to query for the place names. The result of the search from the gazetteer and the feature types are used to construct an ontology of place. The ontology of place is formalized from place name concepts, where each place has a “Part-Of” relationship with its direct parent. The ontology is then formalized in OWL (Web Ontology Language). A search tool prototype is developed that extracts a place name and its parent name from the ontology and use them for searching in Flickr. The semantic richness added to Flickr search engine using our approach is tested and the results are evaluated

The devices, experimental scaffolds, and biomaterials ontology (DEB): a tool for mapping, annotation, and analysis of biomaterials' data

The size and complexity of the biomaterials literature makes systematic data analysis an excruciating manual task. A practical solution is creating databases and information resources. Implant design and biomaterials research can greatly benefit from an open database for systematic data retrieval. Ontologies are pivotal to knowledge base creation, serving to represent and organize domain knowledge. To name but two examples, GO, the gene ontology, and CheBI, Chemical Entities of Biological Interest ontology and their associated databases are central resources to their respective research communities. The creation of the devices, experimental scaffolds, and biomaterials ontology (DEB), an open resource for organizing information about biomaterials, their design, manufacture, and biological testing, is described. It is developed using text analysis for identifying ontology terms from a biomaterials gold standard corpus, systematically curated to represent the domain's lexicon. Topics covered are validated by members of the biomaterials research community. The ontology may be used for searching terms, performing annotations for machine learning applications, standardized meta-data indexing, and other cross-disciplinary data exploitation. The input of the biomaterials community to this effort to create data-driven open-access research tools is encouraged and welcomed.Preprin

OCRonym: Entity Extraction and Retrieval for Scanned Books

In the past five years, massive book-scanning projects have produced an explosion in the number of sources for the humanities, available on-line to the broadest possible audiences. Transcribing page images by optical character recognition makes many searching and browsing tasks practical for scholars. But even low OCR error rates compound into high probability of error in a given sentence, and the error rate is even higher for names. We propose to build a prototype system for information extraction and retrieval of noisy OCR. In particular, we will optimize the extraction and retrieval of names, which are highly informative features for detecting topics and events in documents. We will build statistical models of characters and words from scanned books to improve lexical coverage, and we will improve name categorization and disambiguation by linking document contexts to external sources such as Wikipedia. Our testbed comes from over one million scanned books from the Internet Archive

Content-based image retrieval system for marine invertebrates

There are many marine life around the world where it is essential to have proper documentation for future records. Many information retrieval systems for marine science today require text input from user and can only be accessed online. Therefore, people who do not know the name of the marine species or do not have Internet access cannot search using the systems. Responding to this important need, this work aims to develop a Content-based Image Retrieval (CBIR) system for marine invertebrates based on colour and shape features. With the CBIR system for marine invertebrates, users can use the system to look for marine invertebrates' species instead of using traditional methods of searching such as using books and encyclopedias. Users can easily upload the image of marine invertebrate that they want to search into the system and the system will retrieve all the other similar images of marine invertebrates along with their description. All the system interface's buttons, icons and text were designed in a way where any user can easily understand and further learn to operate the system themselves. Based on the retrieval effectiveness experiment and questionnaire-based survey, the proposed CBIR system for marine invertebrates is shown to be effective, help users search similar images of marine invertebrates, provide concise information on marine invertebrate's species for learning purposes, and is reliable and user-friendly

Event-based personal retrieval

People who work in a research, academic or business environment often have personal information collections which are large enough to need retrieval aids. A major difference between personal information retrieval and normal document retrieval is that the items to be retrieved are often associated with events in the searcher's life and can be retrieved by their relationship to other events as well as by content. This paper describes some of the background to event-based retrieval and then describes a prototype graphical event-based retrieval system