Abstract:Semi-automatic wrapper generation tools aim to ease the task of building structured views over semi-structured web sources. But the wrapper generation techniques presented up to date are unable to properly deal with sources requiring complex navigational sequences for accessing data. In this paper, we present WARGO, a semiautomatic wrapper generation tool, which has been used by nonprogrammer staff to successfully wrap more than 700 commercial web sources in several industrial applications. We describe our approach for wrapper generation and show the difficulties found with other systems for wrapping this kind of sources.

Abstract. The crawler engines of today cannot reach most of the information contained in the Web. A great amount of valuable information is "hidden" behind the query forms of online databases, and/or is dynamically generated by technologies such as JavaScript. This portion of the web is usually known as the Deep Web or the Hidden Web. We have built DeepBot, a prototype hiddenweb crawler able to access such content. DeepBot receives as input a set of domain definitions, each one describing a specific data-collecting task and automatically identifies and learns to execute queries on the forms relevant to them. In this paper we describe the techniques employed for building DeepBot and report the experimental results obtained when testing it with several real world data collection tasks.

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Many HTML pages are generated by software programs by querying some underlying databases and then filling in a template with the data. In these situations the metainformation about the data structure is lost, so automated software programs cannot process these data in such powerful manners as information from databases. We propose a set of novel techniques for detecting structured records in a web page and extracting the data values that constitute them. Our method needs only an input page. It starts by identifying the data region of interest in the page. Then it is partitioned into records by using a clustering method that groups similar subtrees in the DOM tree of the page. Finally, the attributes of the data records are extracted by using a method based on multiple string alignment. We have tested our techniques with a high number of real web sources, obtaining high precision and recall values.