A Survey on Internet Content Transcoding for Universal Access

email:  tchancha@kent.edu,

Prepared for Prof. Javed I. Khan
Department of Computer Science, Kent State University
Date: May 2003

Abstract: This survey presents information about an existing work related to web content transcoding. In this paper presents an overview of different techniques that are available to transcode web contents. There are some works that are commercial products and some works that are still in progress.

Keywords: Transcoding, Annotation

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Table of Contents:




                            What is transcoding? and Why we need it?


                  Basic Transcoding


                  Classification of existing transcoding


                            Semantic transcoding

                                   Syntactic transcoding

                                   Client-side approach

                                   Server-side approach


          Classification Diagram


                  Examples of the existing transcoding system


                            WebAlchemist system

                                   Annotation-based Web content transcoding

                                   Fuzzy-Based Transcoding System

                                   Server-Direct Transcoding

                                   IBM InfoPyramid


                       Open Problem and Research direction




                            Research Papers for More Information on This Topic

                                   Related Links

                                   Research Groups


Scope of Survey




What is transcoding? and Why we need it?


As the incredible growth of mobile communications, the variety of the client devices such as personal digital assistants (PDA), smart phone, hand held PC and WebTV are gaining access to the Internet.[1,7] The Japanese mobile communications company NTT DoCoMo estimates that by 2010, approximate by two thirds of their mobile connections will be from such sources (see table 1). [10]


Connected via mobile

Number (Millions)




Portable PCs

Vending machines, boats, motorcycles, etc.









Table 1. NTT DoCoMo’s Customer Predictions for 2010

(Source: The Economist, October 9,1999) [10]


           Most existing HTML documents are created to be displayed on desktop computers [1,9] and web site designers love to provide complex, detailed content, rich with multimedia experiences.[4] Therefore, the mismatched problem between the client devices decoding capabilities, such as memory, color and display size, and HTML documents encoding requirements is occurred.[2,3,4,7,9]


To cope with the mismatch problem, the different version of the same original HTML document depending on each device capability has been provided [1,4]. The process that provided a content adaptation called transcoding.[9] Moreover, transcoding also includes a new advance function such as user preference and session content.

Transcoding not only provides a content adaptation to match client devices, but also integrates the transcoded result to meet the requirement depending on user preferences such as summarized document and language translator [5]. 

This paper presents an overview of the existing transcoding heuristic and an example of the transcoding system that available.


Basic Transcoding










Figure 1


From figure 1, the different kinds of client devices request the web content. In this case, the transcoding system is running on proxy server. The proxy server requests the information from the origin server after the proxy server receives the original document. The transcoding system selects the suitable transcoding heuristic by considering the device profile, network bandwidth, user preference and so on. After the transcoding system adapts the content such as image, text, video and audio, it sends back the adapted content that match the need and device capability of the user. Finally, the client device can display the content properly.


Classification of existing transcoding


     The existing transcoding heuristic can be classified into two categories:


q      The semantic transcoding [5]. This heuristic use an annotation to provide the guideline information for the transcoding system .


q      The syntactic transcoding. This heuristic use some function to analyze the information from the syntax.


In paper [1], they classified the existing transcoding techniques into two categories: client-side approaches and server-side approach.


q      The client-side approaches : client device received the whole content from the HTTP server and convert the content format locally. The disadvantage is only limited number of transcoding heuristics can be used therefore the quality of transcoded pages is poor. Pixo and Pad ++ are the example of this technique.


q      The server-side approaches : The server-side techniques do not have limitation of client-side techniques and the server-side techniques can do more sophisticated transcoding heuristics than  client-side techniques. Server side-techniques can classified into three groups manual, semi-automatic and fully – automatic techniques.


§        The manual approach , device – specific authoring approach, uses the characteristics of each device in the re-authoring process, so it can produce high quality transcoded page. The disadvantage of these technique is very inconvenient when the device characteristics change or the web page update the corresponding pages must be re-authored.


§        The semi-automatic approach, page filtering, uses the particular keywords or regular expression to annotate web documents. The annotated web page are transcoded base on the annotations. The disadvantage of these technique is good only when user access the page that do not change frequently.


§        The fully automatic approach, automatic re-authoring, re-authors web page in a fully transparent fashion to the web authors. The disadvantage is the poor quality of transcoded pages. The paper [1] suggests the reason behind the poor quality is that existing heuristics ignored the partial semantic information that can be extracted from the syntactic analysis.


Classification Diagram
































Figure 2


           From figure 2, we combine the classification and example of transcoding together. This chart shows the relationship between the transcoding heuristic and transcoding technique.


Examples of the existing transcoding system 


WebAlchemist System  


The first example is WebAlchemist system [1].These system is a part of a HTTP proxy server, and it consists of four main module. The first one is HTML Tokenizer . This module classifies the content of HTML web page into HTML tags and non tags. The second one is Grammar corrector. This module corrects any HTML syntactic errors in the HTML page. The next one is Internal representation generator. This module generates a tree-based internal data representation that is a data structure for transcoding. And the last one is transcoding manager. This module controls decides which heuristic is applied for a given HTML page. After the transcoding procedure is completed, it converted back to the HTML source format.


The WebAlchemist system consists of three improve transcoding Heuristics.

The first one is Selective Elision Transform. The Selective Elision Transform give the elision level on each cell.The cell that have lower elision level is likely to elide. The second one is Restricted First Sentence Elision Transform. This heuristic makes the first sentence of corresponding paragraph into the hyperlink and the whole text block is linked to the first sentence. If the text block is with in a table structure or a text block includes a table structure, the selective elision transform is applied. The last one is Improved Outlining Transform. The original outlining transform applied only between the section header and following text block ,but the improved outlining transform support the relationship between the “UL” and “LI” tag.


The WebAlchemist is base on five transcoding heuristics.[1] They test these system by choosing the different order of transcoding heuristics. The best heuristic order that they found so far are :

1.     The image reduction and elision transforms.

2.     The improved outlining transform

3.     The restricted first sentence elision transform

4.     The indexed segmentation transform

5.     The selective elision.


This group believe that that more semantic information can be extracted by more complete syntactic analysis. Therefore the main future work of these group is to develop more heuristics that can extract semantic information from the syntactic analysis.


Annotation- Based Web Content Transcoding   


The second  example is Annotation- based Web content transcoding. This paper [9] use the idea of applying an annotation to a document depends on the transcoding policy. They use annotations to provide hints  that enable a transcoding engine to make better decision on the content adaptation. The advantage of and annotation-based transcoding approach is the possibility of content adaptation based on semantics. This cannot be archived with existing commercial products, which adapt contents on the basis of web document syntax [9]. They focus on page fragmentation for small screen devices and develop the annotation-based transcoding system on top of a programmable proxy server. They used three types of annotation : alternative, splitting hints and selection criteria to create an annotation file. The transcoding proxy will used this file as a hint to adapt the content. This group give a note that page fragmentation beads on semantic annotation will be more appropriate than page transformation done by solely syntactic information [9].


Fuzzy-Based Transcoding System  


           The third example is a Fuzzy-Based Transcoding System [2]. This system used user and hardware profile, fuzzy rule definitions, set of transcoding specifications, and an XML-based document as input and generates a different XML based document as output. They used user and hardware profile to provide the information of content splitting and visual abilities. In the process of transcoding, the Fuzzy-RDL/TT system is composed of three parts. The first one is fuzzy set definitions. This process will define a set of values that are given from the different device categories. The next one is fuzzy rule definition. This process will use the decision table to create a rule. The last one is transcoding definition. This process used the previous definition and rule to create the transcoding function. After that, they use the transcode rule to delete node, insert node, replace node, assign a new name to replace with link. The transcoding functions are specified by a Java oriented language with operate on the DOM tree representation of and XML-base document [2].Currently, this system only have transcoding definition for complete HTML to C-HTML and to WML for PDA. They have a few rules for small phones and smart phone. They also investigate a combined transcoding to C-HTML and VoiceML with speech synthesis [2].


Server-Direct Transcoding   


The fourth one is Server-direct transcoding [4]. In this approach, the original server provide explicit duidance to the transcoding system such as client or proxy. They believe that the traditional transcoding breaks the end-to-end model of the web, because the proxy does not know the sematics of the content. Server-directed transcoding preserves end-to-end semantics while supporting aggressive content transfomation [5]. They provide the transcoding guidance by defining a new HTTP header and using the transcoding  applet as a guidance.


IBM InfoPyramid  


           The last one is IBM InfoPyramid. The system retrieves and analyzes  the Internet content and convert them into the InfoPyramid format. A policy engine gathers the capabilities of the client, the network conditions, and the transcoding preferences of the user and publisher [7,8] This information is used to define the transcoding options for the client. They used this idea in their product named as IBM WebSphere [11,12]. The IBM WebSphere Transcoding Publisher is network software that modifies content presented to user based on the information associated with the request, such as device constraints, network constraints, user preferences and organizational policies. The IBM WebSphere Transcoding Publisher product provides a framework for proxy transcoding plug-ins, using Java applets and library of built-in transformations [4].




           From the examples, we can see that the current transcoding system is mostly executed on proxy server and some transcoding system use origin server to provide a hints to adapt content at proxy server. Some said that server can provide the complete information and intention for producing a good quality of  the  transcoding by using semantic transcoding. Another said that if they can get enough information form the syntax analysis, they can generated the good quality of  the transcoding output. In the server transcoding approach, There are some trade-off. One of them is an extra connection for downloading the hints from original server such as annotation file and transcoding applet. While the proxy transcoding approach with syntax analysis is lack of important information from origin server.


Open Problem and Research direction


  1. Extreme Transcoding in iso-format xcoding (regular web page to cell phone display xcoding).
  2. Orthogonal format xcoding (visual to completely voice based xcoding).
  3. Hyperspace Overview: summary fusion from multiple linked pages.
  4. Layout and placement organization in composite pages.
  5. Xcoding performance for multimedia content.




Research Papers for More Information on This Topic


[1]       Y. Whang, C. Jung, J. Kim and S. Chung "WebAlchemist: A Web Transcoding System for Mobile Web Access in Handheld Devices", In Proc. of  SPIE Vol. #4534,Aug 2001.

[2]       R. Schaefer, A Dangberg, W. Mueller. “Fuzzy Rules for the Transcoding of HTML Files.” HICSS 35, Hawaii,USA, Jan 2002.

[3]       A. Singh, A. Trivedi and K. Ramamritham. “PTC : Proxies that Transcode and Cache in Heterogeneous Web Client Environments”, WISE 2002, Singapore, Dec 12 - 14, 2002.

[4]       J.C. Mogul, "Server-Directed Transcoding", Computer Communications 24(2):, pp.155-162, Feb. 2001.

[5]       B. Knutsson, H. Lu and J. Mogul, "Architecture and Pragmatics of Server-Directed Transcoding", Proc. 7th International Workshop on Web Content Caching and Distribution, Boulder, Colorado, August 2002.

[6]       K. Nagao,”Semantic Transcoding: Making the World Wide Web More Understandable and Usable with External Annotations”, In Proc. of International Conference on Advanced in Infrastructure for Electronic Business, Science, and Education on the Internet ,2000.

[7]       J. Smith and R. Mohan and C. Li,” Transcoding Internet content for heterogeneous client devices”, Proc. IEEE Int. Conf on Circuits and Syst.(ISCAS), May 1998.

[8]       R. Mohan, J. Smith, C.-S. Li,  "Adapting Multimedia Internet Content For  Universal Access", IEEE Transactions on Multimedia, pp.  104-114, March 1999.

[9]       Hori M., Kondoh G., Ono K., Hirose S. and Singhal S. “Annotation-based web content transcoding”. In Proc. of Ninth Internetional WWW Conference, pp. 197–211, 2000.

[10]   Chris B,”Practical WAP : developing applications for the wireless web”, Cambridge University press,2001,ISBN 0 521 00561 2.


Related Links


[11]   IBM Research.

[12]   WebSphere Software


Research Groups


-         IBM Research Laboratory

-         Compaq Computer Corporation Western Research Laboratory




           This survey is based on electronic search in OhioLink’s Electronic Journal Center, ACM Digital Library and IEEE Computer Society Digital Library.

 The keywords that used for searching are “transcoding”, “web transcoding” and “annotation”.