A geo-temporal information extraction service for processing descriptive metadata in digital libraries

In the context of digital map libraries, resources are usually described according to metadata records that define the relevant subject, location, time-span, format and keywords. On what concerns locations and time-spans, metadata records are often incomplete or they provide information in a way that is not machine-understandable (e.g. textual descriptions). This paper presents techniques for extracting geotemporal information from text, using relatively simple text mining methods that leverage on a Web gazetteer service. The idea is to go from human-made geotemporal referencing (i.e. using place and period names in textual expressions) into geo-spatial coordinates and time-spans. A prototype system, implementing the proposed methods, is described in detail. Experimental results demonstrate the efficiency and accuracy of the proposed approaches

Harvesting Entities from the Web Using Unique Identifiers -- IBEX

In this paper we study the prevalence of unique entity identifiers on the Web. These are, e.g., ISBNs (for books), GTINs (for commercial products), DOIs (for documents), email addresses, and others. We show how these identifiers can be harvested systematically from Web pages, and how they can be associated with human-readable names for the entities at large scale. Starting with a simple extraction of identifiers and names from Web pages, we show how we can use the properties of unique identifiers to filter out noise and clean up the extraction result on the entire corpus. The end result is a database of millions of uniquely identified entities of different types, with an accuracy of 73--96% and a very high coverage compared to existing knowledge bases. We use this database to compute novel statistics on the presence of products, people, and other entities on the Web.Comment: 30 pages, 5 figures, 9 tables. Complete technical report for A. Talaika, J. A. Biega, A. Amarilli, and F. M. Suchanek. IBEX: Harvesting Entities from the Web Using Unique Identifiers. WebDB workshop, 201

Sample-based XPath Ranking for Web Information Extraction

Web information extraction typically relies on a wrapper, i.e., program code or a configuration that specifies how to extract some information from web pages at a specific website. Manually creating and maintaining wrappers is a cumbersome and error-prone task. It may even be prohibitive as some applications require information extraction from previously unseen websites. This paper approaches the problem of automatic on-the-fly wrapper creation for websites that provide attribute data for objects in a ‘search – search result page – detail page’ setup. The approach is a wrapper induction approach which uses a small and easily obtainable set of sample data for ranking XPaths on their suitability for extracting the wanted attribute data. Experiments show that the automatically generated top-ranked XPaths indeed extract the wanted data. Moreover, it appears that 20 to 25 input samples suffice for finding a suitable XPath for an attribute