Mining data records in Web pages

Abstract

A large amount of information on the Web is contained in regularly structured objects, which we call data records. Such data records are important because they often present the essential information of their host pages, e.g., lists of products or services. It is useful to mine such data records in order to extract information from them to provide value-added services. Existing automatic techniques are not satisfactory because of their poor accuracies. In this paper, we propose a more effective technique to perform the task. The technique is based on two observations about data records on the Web and a string matching algorithm. The proposed technique is able to mine both contiguous and noncontiguous data records. Our experimental results show that the proposed technique outperforms existing techniques substantially.

Data Extraction and Alignment by using Combining Tag and Values Similarity

“…They focus on two things those are, Data records recognition from the query page and next is arrange these extracted data in a table. Robert Grossman, YanhongZhai, Bing Liu [4], mainly focused on the data record which contains the large amount of information on the web. Data records also contain the information regarding their host pages for example list of product or services.…”

“…In Record Extraction phase, firstly it identifies the data region which contains the number of query result records and then it does the segmentation of records [4]. Record alignment steps properly align the extracted data in a structured manner means it arrange the all the extracted QRR's in a table.…”

“…In this section first we recognize the data regions in query page which contains numerous data records [4] [7]. Some child sub tree of the same parent node, here node is nothing but the HTML tags which forms data regions which is having data records.…”

A Holistic Solution for Duplicate Entity Identification in Deep Web Data Integration

“…At present, many issues in the field of deep Web data integration, such as interface integration [2] [3] and Web data extraction [4,5], have been widely studied. However, as a necessary step, identifying the duplicate entities(records) from multiple Web databases has not received due attention yet.…”

NET – A System for Extracting Web Data from Flat and Nested Data Records

“…A similar method is proposed in [11]. [7] and [15] propose some algorithms to identify data records, which do not extract data items from the data records, and do not handle nested data records. Our previous system DEPTA [13] is able to align and extract data items from data records, but does not handle nested data records.…”