IMPORTANT OF ANALYZER

Writing KDE4 file analyzers

2009-06-30T07:43:00.000-07:00

File analyzers extract data from files to display in the file dialogs and file managers. The data gathered this way is also used to search for files. KDE4 allows the use of multiple analyzers per file type. Analyzers can extract text which is used for indexing, but they can also retrieve other data such as song title, album title, recipient, md5 sum, the mimetype of a file, and much more.

This tutorial describes how you can write new analyzers.

[edit] Primer

[edit] What are file analyzers?

A file analyzer is a class that extracts metadata from a file or data stream. You can have file analyzers that are specific for certain file types such as an analyzer that extracts the information from an ogg vorbis file. There are also more general file analyzers that calculate for example the md5 or sha1 of a file.

[edit] File analyzers in KDE4

KDE4 uses stream based file analyzers for retrieving text and metadata from files. This has a number of advantages over file based methods. Stream based access

is faster for 90% of the file types,
allows easy analysis of embedded files such as email attachments or entries from zip files, rpms and many other container file formats.

Writing stream-based analyzers requires a different approach than the usual file-based methods and in the tutorial we will explain how to go about it.

The current state of porting the KDE3 kfile plugins to KDE4 stream analyzers can be seen at

Look for existing code

If you want to see some code examples, take a look at the already implemented file analyzers at

Some examples of meta-data extraction from files can also be found.

Choosing the type of analyzer

There are two main types of analyzers: StreamThroughAnalyzer and StreamEndAnalyzer. The latter is more powerful and a bit easier to program, but has a limitation: only one StreamEndAnalyzer can analyze a particular resource, while you can use as many StreamThroughAnalyzers as you like. Most analyzers can be written as StreamThroughAnalyzers. The most important exception is for analyzers that extract embedded resources from a stream. Examples of this are the ZipEndAnalyzer, the MailEndAnalyzer and the RpmEndAnalyzer.

In this tutorial we focus on a simple example file type: BMP images. The information we will get from this file is located at the start of the file. It turns out that in this case, it is just as easy to implement the analyzer as a StreamEndAnalyzer as a StreamThroughAnalyzer. We will implement it as a StreamEndAnalyzer and point out how to do the same as a StreamThroughAnalyzer.

Two other types of stream analyzers have been added to Strigi. StreamLineAnalyzer, for file format based on lines of plan text, StreamSaxAnalyzer, for XML based file such as SVG.

[edit] StreamEndAnalyzer

Three functions need to be implemented in a StreamEndAnalyzer:

name()
checkHeader()
analyze()

Wusage Web Server Log Analyzer

2009-06-30T07:42:00.001-07:00

Wusage Web Server Log Analyzer Review
Wusage analyzes the logs produced by your web server and producesattractive HTML reports, complete with 3D bar charts and pie charts. Reports can also be delivered by email. By measuring the popularity ofyour documents, as well as identifying the sites that access your servermost often, Wusage provides valuable marketing information. By determiningthe paths your users follow and analyzing the sites from which they come,Wusage helps you find out which outside sites are most important to you.The latest release of our web server log analyzer is now available forLinux, the Windows family of operating systems, and many Unix platforms.New features include a powerful new "ISP mode" with support for automaticlog rotation and generation for dozens and even hundreds of virtualdomains. Individual virtual domain holders can log in and edit their ownsettings in a safe, restricted environment. In addition, a user-friendly"simple mode"has been added for users responsible for only a single web site.

Google pagerank analysis tool

2009-06-30T07:40:00.000-07:00

Advanced Page Rank Analyzer is the search engine optimization software designed for retrieving Google pagerank values for a list of web sites (URLs). This pagerank tool also finds the number of inbound links for each URL and checks each web site for availability in the Google Catalog and DMOZ and Yahoo directories. There are two types of pagerank reports available. You can view the average values of all ranking parameters for a list of URLs and the detailed ranking information for each web site on the list.

While optimizing a web site, it is often necessary to evaluate the competition level for one or another search phrase. Other time, it may be interesting to find out the PageRank of pages referring to your web site. In all of such cases, analysis of great number of URLs is required for determining their search ranking. Performing this task manually may appear too labor-intensive. At the same time, our pagerank tool allows performing the required analysis within a few minutes!

Our Google PageRank analysis tool allows checking the following ranking parameters:

- Number of inbound (backward) links - based on data from several search engines.

- Web site availability in the Google Catalog, DMOZ and Yahoo directories

Advanced Page Rank analyzer can also extract URLs for specified search queries from Google, Yahoo, AltaVista, MSN Search and AllTheWeb. Therefore, you can collect the URL list for selected search phrase and then analyze it with our pagerank analysis tool.

The complete list of this pagerank software's features can be found in the section.

Additional software required for working with Advanced Page Rank Analyzer is: Internet Explorer - version 5.5 or greater, Google ToolBar.
The Google ToolBar is a toolbar you can use when you are running Internet Explorer. After its installation you will be able to see the PageRank (PR) of a page. It can range from 0 (not important page according to Google) to 10 (very important page according to Google). This feature is included when installing the Google ToolBar with advanced features.

Below is some overall information on Google Page Rank:

The Google website explains PageRank as: PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages "important."

Important, high-quality sites receive a higher PageRank, which Google remembers each time it conducts a search. Of course, important pages mean nothing to you if they don't match your query. So, Google combines PageRank with sophisticated text-matching techniques to find pages that are both important and relevant to your search. Google goes far beyond the number of times a term appears on a page and examines all aspects of the page's content (and the content of the pages linking to it) to determine if it's a good match for your query.

While the exact algorithm of each search engine is a closely guarded secret, search engine analysts believe that the search engine results (ranking) is some form of a multiplier factor of 'Page Relevance' and 'PageRank'. Simply put, the formula would look something like -

Ranking = (Page Relevance) x (PageRank)

The PageRank logic made sense and the algorithm seemed impregnable at the hands of the webmasters. The search results of Google search have demonstrated high relevance and this is one of the main reasons for their resounding success. Most other major search engines have adopted this logic in their own algorithms in some form or the other, varying the importance they assign to this value in ranking sites in their search engine result pages.

Since the early days of the web, search engines have constantly tried to evolve better algorithms to rank relevant web pages. Most search engines give significant importance to as a criterion for evaluating importance of web pages ranking and indexing purposes.