38 research outputs found
An Architecture for Efficient Web Crawling
Virtual Integration systems require a crawling tool able to
navigate and reach relevant pages in the Deep Web in an efficient way.
Existing proposals in the crawling area fulfill some of these requirements,
but most of them need to download pages in order to classify them as
relevant or not. We propose a crawler supported by a web page classifier
that uses solely a page URL to determine page relevance. Such
a crawler is able to choose in each step only the URLs that lead to
relevant pages, and therefore reduces the number of unnecessary pages
downloaded, minimising bandwidth and making it efficient and suitable
for virtual integration systems.Ministerio de Educación y Ciencia TIN2007-64119Junta de Andalucía P07-TIC-2602Junta de Andalucía P08- TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010-21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-
On using high-level structured queries for integrating deep-web information sources
The actual value of the Deep Web comes from integrating the data its applications provide. Such applications offer human-oriented search forms as their entry points, and there exists a number of tools that are used to fill them in and retrieve the resulting pages programmatically. Solution that rely on these tools are usually costly, which motivated a number of researchers to work on virtual integration, also known as metasearch. Virtual integration abstracts away from actual search forms by providing a unified search form, i.e., a programmer fills it in and the virtual integration system
translates it into the application search forms. We argue that virtual integration costs might be reduced further if another abstraction level is provided by issuing structured queries in high-level languages such as SQL, XQuery or SPARQL; this helps abstract away from search forms. As far as we know, there
is not a proposal in the literature that addresses this problem. In this paper, we propose a reference framework called IntegraWeb to solve the problems of using high-level structured queries to perform deep-web data integration. Furthermore, we provide a comprehensive report on existing proposals from the database integration and the Deep Web research fields, which can be used in combination to address our problem within the previous
reference framework.Ministerio de Ciencia y Tecnología TIN2007-64119Junta de Andalucía P07- TIC-2602Junta de Andalucía P08-TIC-4100Ministerio de Ciencia e Innovación TIN2008-04718-EMinisterio de Ciencia e Innovación TIN2010- 21744Ministerio de Economía, Industria y Competitividad TIN2010-09809-EMinisterio de Ciencia e Innovación TIN2010-10811-EMinisterio de Ciencia e Innovación TIN2010-09988-
Searching dynamic Web pages with semi-structured contents
At present, information systems (IS) in higher education are usually supported by databases (DB) and accessed through a Web interface. So happens with SiFEUP, the IS of the Engineering Faculty of the University of Porto (FEUP). The typical SiFEUP user sees the system as a collection of Web pages and is not aware of the fact that most of them do not exist in the sense of being an actual HTML file stored in a server but corresponds to HTML code generated on the fly by a designated program that accesses the DB and brings the most up-to-date information to the user desktop. Typical search engines do not index dynamically generated Web pages or just do that for those that are specifically mentioned in a static page and do not follow on the links the dynamic page may contain. In this paper we describe the development of a search facility for SiFEUP, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, plus meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation.At present, information systems (IS) in higher education are usually supported by databases (DB) and accessed through a Web interface. So happens with SiFEUP, the IS of the Engineering Faculty of the University of Porto (FEUP). The typical SiFEUP user sees the system as a collection of Web pages and is not aware of the fact that most of them do not exist in the sense of being an actual HTML file stored in a server but corresponds to HTML code generated on the fly by a designated program that accesses the DB and brings the most up-to-date information to the user desktop. Typical search engines do not index dynamically generated Web pages or just do that for those that are specifically mentioned in a static page and do not follow on the links the dynamic page may contain. In this paper we describe the development of a search facility for SiFEUP, how the limitations put to indexing dynamic Web pages were circumvented, and an evaluation of the results obtained. The solution involves using a locally developed crawler, the Oracle Text full text indexer, plus meta-information automatically drawn from the DB or manually added to improve the relevance factor calculation
Web Data Extraction, Applications and Techniques: A Survey
Web Data Extraction is an important problem that has been studied by means of
different scientific tools and in a broad range of applications. Many
approaches to extracting data from the Web have been designed to solve specific
problems and operate in ad-hoc domains. Other approaches, instead, heavily
reuse techniques and algorithms developed in the field of Information
Extraction.
This survey aims at providing a structured and comprehensive overview of the
literature in the field of Web Data Extraction. We provided a simple
classification framework in which existing Web Data Extraction applications are
grouped into two main classes, namely applications at the Enterprise level and
at the Social Web level. At the Enterprise level, Web Data Extraction
techniques emerge as a key tool to perform data analysis in Business and
Competitive Intelligence systems as well as for business process
re-engineering. At the Social Web level, Web Data Extraction techniques allow
to gather a large amount of structured data continuously generated and
disseminated by Web 2.0, Social Media and Online Social Network users and this
offers unprecedented opportunities to analyze human behavior at a very large
scale. We discuss also the potential of cross-fertilization, i.e., on the
possibility of re-using Web Data Extraction techniques originally designed to
work in a given domain, in other domains.Comment: Knowledge-based System
Big data warehouse framework for smart revenue management
Revenue Management’s most cited definitions is probably “to sell the right accommodation to the
right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”.
Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques
for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as
revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data,
followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse
necessary to produce high quality business intelligence and analytics. This will be achieved through the
collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage
framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available
information, in the present case, it was focus only the extraction of information from the web by a web crawler
– raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a
set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational
database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will
be the principal focus of the paper. In this context, clues will also be giving how to compile information for
Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make
it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue
Managemen
Framework for a Hospitality Big Data Warehouse: The Implementation of an Efficient Hospitality Business Intelligence System
order to increase the hotel's competitiveness, to maximize its revenue, to meliorate its online reputation and improve customer relationship, the information about the hotel's business has to be managed by adequate information systems (IS). Those IS should be capable of returning knowledge from a necessarily large quantity of information, anticipating and influencing the consumer's behaviour. One way to manage the information is to develop a Big Data Warehouse (BDW), which includes information from internal sources (e.g., Data Warehouse) and external sources (e.g., competitive set and customers' opinions). This paper presents a framework for a Hospitality Big Data Warehouse (HBDW). The framework includes a (1) Web crawler that periodically accesses targeted websites to automatically extract information from them, and a (2) data model to organize and consolidate the collected data into a HBDW. Additionally, the usefulness of this HBDW to the development of the business analytical tools is discussed, keeping in mind the implementation of the business intelligence (BI) concepts.SRM QREN IDT [38962]FCT projects LARSyS [UID/EEA/50009/2013]CIAC [PEstOE/EAT/UI4019/2013]CEFAGE [PEst-C/EGE/UI4007/2013]CEG-IST - Universidade de Lisboainfo:eu-repo/semantics/publishedVersio
From Wrapping to Knowledge
One the most challenging problems for Enterprise Information Integration is to deal with heterogeneous information
sources on the Web. The reason is that they usually provide information that is in human-readable form only, which makes it difficult for
a software agent to understand it. Current solutions build on the idea of annotating the information with semantics. If the information is
unstructured, proposals such as S-CREAM, MnM, or Armadillo may be effective enough since they rely on using natural language
processing techniques; furthermore, their accuracy can be improved by using redundant information on the Web, as C-PANKOW has
proved recently. If the information is structured and closely related to a back-end database, Deep Annotation ranges among the most
effective proposals, but it requires the information providers to modify their applications; if Deep Annotation is not applicable, the
easiest solution consists of using a wrapper and transforming its output into annotations. In this paper, we prove that this
transformation can be automated by means of an efficient, domain-independent algorithm. To the best of our knowledge, this is the first
attempt to devise and formalize such a systematic, general solution.Comisión Interministerial de Ciencia y Tecnología TIC2003-02737-C02-0
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
New Methods and Tools for the World Wide Web Search
Explosive growth of the World Wide Web as well as its heterogeneity call for powerful and easy to use search tools capable to provide the user with a moderate number of relevant answers. This paper presents analysis of key aspects of recently developed Web search methods and tools: visual representation of subject trees, interactive user interfaces, linguistic approaches, image search, ranking and grouping of search results, database search, and scientific information retrieval. Current trends in Web search include topics such as exploiting Web hyperlinking structure, natural language processing, software agents, influence of XML markup language on search efficiency, and WAP search engines
Development of Multilingual Resource Management Mechanisms for Libraries
Multilingual is one of the important concept in any library. This study is create on the basis of global recommendations and local requirement for each and every libraries. Select the multilingual components for setting up the multilingual cluster in different libraries to each user. Development of multilingual environment for accessing and retrieving the library resources among the users as well as library professionals. Now, the methodology of integration of Google Indic Transliteration for libraries have follow the five steps such as (i) selection of transliteration tools for libraries (ii) comparison of tools for libraries (iii) integration Methods in Koha for libraries (iv) Development of Google indic transliteration in Koha for users (v) testing for libraries (vi) results for libraries. Development of multilingual framework for libraries is also an important task in integrated library system and in this section have follow the some important steps such as (i) Bengali Language Installation in Koha for libraries (ii) Settings Multilingual System Preferences in Koha for libraries (iii) Translate the Modules for libraries (iv) Bengali Interface in Koha for libraries. Apart from these it has also shows the Bengali data entry process in Koha for libraries such as Data Entry through Ibus Avro Phonetics for libraries and Data Entry through Virtual Keyboard for libraries. Development of Multilingual Digital Resource Management for libraries by using the DSpace and Greenstone. Management of multilingual for libraries in different areas such as federated searching (VuFind Multilingual Discovery tool ; Multilingual Retrieval in OAI-PMH tool ; Multilingual Data Import through Z39.50 Server ). Multilingual bibliographic data edit through MarcEditor for the better management of integrated library management system. It has also create and editing the content by using the content management system tool for efficient and effective retrieval of multilingual digital content resources among the users