The Lixto Project: Exploring New Frontiers of Web Data Extraction

Carme, Julien; Ceresna, Michal; Frölich, Oliver; Gottlob, Georg; Hassan, Tamir; Herzog, Marcus; Holzinger, Wolfgang; Krüpl, Bernhard

doi:10.1007/11788911_1

Cited by 11 publications

(7 citation statements)

References 11 publications

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“…Some approaches employed ML techniques like HMMs and classifiers, but the general rationale has been to arrive at a set of good extraction rules that could be applied in a deterministic manner. Early prototype systems of this kind included Rapier [28] and the W4F toolkit [112]; more recent systems that are being pursued further include Lixto [14,30,70], RoadRunner [43,44], and SEAL [135].…”

Section: Rule/query-based Methodsmentioning

confidence: 99%

From information to knowledge

Weikum

Theobald

2010

Proceedings of the Twenty-Ninth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems

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There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. Recent endeavors of this kind include DBpedia, EntityCube, KnowItAll, ReadTheWeb, and our own YAGO-NAGA project (and others). The goal is to automatically construct and maintain a comprehensive knowledge base of facts about named entities, their semantic classes, and their mutual relations as well as temporal contexts, with high precision and high recall. This tutorial discusses state-ofthe-art methods, research opportunities, and open challenges along this avenue of knowledge harvesting.

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Section: Rule/query-based Methodsmentioning

confidence: 99%

From information to knowledge

Weikum

Theobald

2010

Proceedings of the Twenty-Ninth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems

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“…That work is described in [6]- [8]. Currently, the scope of the Lixto project has been extended to additional research in the field of fully automated and unsupervised Web data extraction [9]. The supervised work of the Lixto project focuses on data extraction from deep Web pages which includes the challenge of form filling and the navigation on Web pages.…”

Section: Scientific Approachesmentioning

confidence: 99%

A Web Application for the Collection and Comparison of E-Shop Product Data

2016

Proceedings of 2016 the 6th International Workshop on Computer Science and Engineering

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E-commerce is a highly competitive and constantly growing market. On-line retailers need to compare their product offers with those of their competitors in order to remain competitive. Due to the large range of product offers on the Web and the fact that internet prices are adjusted on a daily basis or even more frequently the manual comparison of on-line product offers is a very time consuming task. Therefore, on-line retailers prefer the use of automated tools for performing that work. There are many existing ready-to-use software tools and on-line services from price comparison websites to market intelligence tools, but those tools still require a greater effort for the configuration of the tool or the comparison of the offers. The contribution of this paper is a Web application to automatically identify, extract and compare the product offers of the own e-shop with those of defined competitors. The specialties of the presented Web application are its degree of automation and the little effort for configuration.

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“…21 use document understanding techniques for identifying atomic elements of PDF documents on which apply spatial reasoning and wrapping techniques that enable to identify significant document blocks; Gottlob et Al. in 22 describe the PDF document preprocessing techniques currently used in the LixTo system. Before the Gottlob's papers only document understanding 23 and table recognition methods 24 was applied on PDF documents in attempting to identify and extract relevant information from them.…”

Section: Related Workmentioning

confidence: 99%

Ontology-Based Information Extraction From PDF Documents With Xonto

Oro

Ruffolo

Saccà

2009

Int. J. Artif. Intell. Tools

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Information extraction is of paramount importance in several real world applications in the areas of business, competitive and military intelligence because it enables to acquire information contained in unstructured documents and store them in structured forms. Unstructured documents have different internal encodings, one of the most diffused encoding is the visualization-oriented Adobe portable document format (PDF). Although several sophisticated and indeed complex approaches were proposed, they are still limited in many aspects. In particular, existing information extraction systems cannot be applied to PDF documents because of their completely unstructured nature that pose many issues in defining IE approaches. In this paper the novel ontology-based system named XONTO, that allows the semantic extraction of information from PDF documents, is presented. The XONTO system is founded on the idea of self-describing ontologies in which objects and classes can be equipped by a set of rules named descriptors. These rules represent patterns that allow to automatically recognize and extract ontology objects contained in PDF documents also when information is arranged in tabular form. This way a self-describing ontology expresses the semantic of the information to extract and the rules that, in turn, populate itself. In the paper XONTO system behaviors and structure are sketched by means of a running example.

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The Lixto Project: Exploring New Frontiers of Web Data Extraction

Cited by 11 publications

References 11 publications

From information to knowledge

From information to knowledge

A Web Application for the Collection and Comparison of E-Shop Product Data

Ontology-Based Information Extraction From PDF Documents With Xonto

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