Designing Summary Tables for Mining Web Log Data

In the Web, the data is generally gathered automatically by Web servers and collected in server or access logs. However, as users access larger and larger amounts of data, query response times to extract information inevitably get slower. A method to resolve this issue is the use of summary tables. In this short note, we design a prototype of summary tables that can efficiently extract information from Web log data. We also present the relative performance of the summary tables against a sampling technique and a method that uses raw data.