How to Evaluate the Effectiveness of URL Normalizations Snag Ho Lee, Sung Jin Kim, Hyo Sook Jeong in Proceedings of the Third International Conference on HIS

Contents  Abstract  Introduction  URL Normalizations  Evaluation of a URL Normalization Method  Empirical Evaluation  Conclusions and Future Works

Abstract  Syntactically different URLs could represent the same web page  Duplicate representation handle a large amount of same web pages unnecessarily  URL normalization helps eliminate duplicate URLs  In this paper  presents a method that evaluates the effectiveness of a URL normalization method

Introduction  URL (Uniform Resource Locator)  A string that represents a web resource (a web page)  Equivalent URL  If more than two URLs locate the same web page  The inability to recognize two equivalent URLs being equivalent gives rise to a large amount of processing overhead

Introduction (2)  False negative  Determining equivalent URLs not to be equivalent  False positive  Determining non-equivalent URLs to be equivalent

Introduction (3)  URL normalizations [5]  Transform syntactically different but equivalent URLs into a syntactically identical string  The three types of URL normalizations  syntax-based normalization  scheme-based normalization  protocol-based normalization  The first two types of normalizations reduce false negatives while strictly avoiding false positives  Standard community does not give specific methods for the protocol-based normalization [6]

Introduction (4)  Extended normalization methods (1) [6]  Changing letters in the path component into the lower- case letters or into the upper-case letters  >  Attaching and eliminating the “www” prefix to URLs with and without the prefix in the host component   Eliminating the last slash symbol from URLs   Eliminating default page names in the path component 

Introduction (5)  Extended normalization methods (2)  Allow false positives  Lose, gain, or change web pages unintentionally  Reduce the number of total URLs in operation  Presents a scheme to evaluate the effectiveness of URL normalization methods  URL reduction rate  Web page loss/gain/change rate  94 million URLs (20,799 web sites in Korea)  Help select normalization methods

URL Normalizations  URL components  scheme : protocol (here, Hypertext Transfer Protocol)  authority : user information, host, port  path : directories  query : parameter names, values  fragment : particular part of a document

Standard URL Normalizations  A process that transforms a URL into a canonical form  syntax-based normalization  Characters in the scheme and host components into lower- case letters  ->  All unreserved characters (i.e., uppercase and lowercase letters, decimal digits, …) should be decoded  ->  path segment “.” and “..” are removed appropriately  ->

Standard URL Normalizations (2)  Scheme-based normalization  Default port number is truncated from the URL  ->  If path string is null, then the path string is transformed into “/”  ->  Fragment in the URL is truncated  ->  Protocol-based normalization  result of accessing the resources  the common conventions of their scheme’s dereference algorithm  ->

Extended URL Normalizations  Standard Normalization  No false positive  High possibility of false negatives  In web applications (such as web crawlers)  handle a huge number of URLs  reducing the possibility of false negatives implies reduction of URLs that need to be considered    Extended URL Normalization  Significantly reduce the possibility of false negatives  Allow false positives on a limited level  How to evaluate the effectiveness of an extended normalization method precisely ?

Evaluation of a URL Normalization Method  Two different points of view  how much URLs are reduced  how many pages are lost, gained, or changed  Suppose  Transform a given URL u1 in the original form into a URL u2 in a canonical form  The u1 and u2 locate web page p1 and p2 on the web, respectively  There are totally ten cases to consider

Evaluation of a URL Normalization Method (2)  Lose a web page (2, 4, 9)  Gain a web page (8) or Get a different page (7)  Negative false (2, 4, 7, 8, 9)

Evaluation of a URL Normalization Method (3)  (1) Page p1 exists on the web  (A) Page p2 does not exist (4, 9)  False positive, lose one page p1  (B) Page p2 exists, p1 & p2 same page (1, 6)  No false positive, save one page request  (C) Page p2 exists, p1 & p2 are not same (7, 2)  False positive, loss (2) or loss & gain (7)  (2) Page p1 does not exist  (A) URL u2 is already known to us (3, 5)  Do not loss any pages, save one page request  (B) URL u2 is not known to us (8, 10)  Gain one web page (8), lose nothing (10)  The number of page requests remains unchanged

Evaluation of a URL Normalization Method (4)  For evaluating the effectiveness of the URL normalization, we propose a number of metrics  Let N be the total number of URLs that are considered  Page loss rate = the total number of lost pages / N.  Page gain rate = the total number of gain pages / N  Page change rate = the total number of change pages / N  Page non-loss rate = the total number of non-loss pages / N  Reduction of URL  URL reduction rate = 1 - (the unique number of URLs after normalization / the unique number of URLs before normalization)  If we normalize 100 distinct URLs into 90 distinct URLs  The URL reduction rate is 0.1 (1 -90/100, or 10%)  A good normalization method  A high value of URL reduction rate  low values of page loss/gain/change