Personal, Private Movie Recommender System at the Semantic Web Challenge

I advised together with Gerald Reif the master thesis of Tobias Bannwart about a personal cross-site movie recommender system that is implemented as Firefox add-on. The add-on is known as OMORE and can be downloaded. We decided to bring OMORE to market maturity. For this, we had to rethink its architectural design and usability and beside from its advantages we came up with the following open challenges:

  1. Movie cross-references: It is not known what movie of one provider corresponds to what other movie page of another provider. Providers may be commercial pages like, review pages like or knowledge bases such as
  2. Retrieval of movie cross-references: No flexible search service exists to retrieve movie cross-references based on movie title and release year information.
  3. Maintenance of movie cross-references: A vast amount of potential movie cross-references exists that is difficult to gathered with a Web crawler approach. In addition, the set of movie pages increases fast.

We came up with the following solutions:

  1. Movie cross-references: A knowledge base is needed to persist movie cross-references. Concretely, for all movies the information of (1) what movie pages represent the movie as its content and (2) what movie pages represent the commercial product of a movie such as DVD, Blu-Ray, VHS or even Video-On-Demand (VoD). This semantical distinction has to be done, because a movie represented in VHS and Blu-Ray are not the same but show the same movie. Therefore, we decided to apply Semantic Web technologies to persist movie cross-references. We applied D2R that maps data from a relational database management system to RDF. RDF is the basic format to represent resources semantically. Our knowledge base of movie cross-references is called LiMo.
  2. Retrieval of movie cross-references: A search service has to be provided, that is able to provide even fuzzy search on the movie cross-references knowledge base. We reason for fuzzy search because the movie are presented quite heterogeneously among different Web pages. Movie titles may be misspelled, transformed or even extended in various way. Especially on online shops, we experienced that the movie titles are extended with information about many variants of special or collector’s edition and the type of medium the movie is provided. Instead of trying to extract the original title from the unpurified title, we decided to apply fuzzy search over movie titles and release year to retrieve movies. Our movie retrieval service can be accessed at MOLookup.
  3. Maintenance of movie cross-references: A Web crawler approach is not feasible due to the time latency and the need for resources. Thus, we decided to invent a collaborative approach. Whenever a user browses a new movie Web page that is not yet cross-referenced with LiMo, OMORE automatically uses the movie retrieval services MOLookup and provides the current URL of the new movie page. Then, this URL is cross-referenced to the retrieved movie. With that approach we automatically gather all the relevant movie cross-references with the user’s help. This way, normal users even contribute to the Semantic Web without knowing it.

With this new approach, we decided to participate in the this year’s Semantic Web Challenge that is co-located with the International Semantic Web Conference 2009 (ISWC) in Washington D.C. We were 16 participants that made it to the Semantic Web Challenge in Washington D.C. We presented our movie recommender system and its revised architecture besides the official Poster and Demonstrations session the main conference. Our secret weapon to attract many people to our stand was Swiss chocolate. And well, it worked out ;). The official time for the challenge presentation was 19:15-21:15. But people already showed up to our stand at half past 6 and kept coming by until 10 in the evening. One reason my be of course the chocolate ;), but also the viral marketing that people started that saw our challenge. Overall, people were really excited about our personal and private movie recommender system that even provides cross-site movie recommendations.
Despite the great success, we didn’t made it to finals. However, the challenge was a really nice experience and we had still have the great success having people excited about our OMORE.


Online stores and Web portals bring information about a myriad of items such as books, CDs, restaurants or movies at the user’s fingertips. Although, the Web reduces the barrier to the information, the user is overwhelmed by the number of available items. Therefore, recommender systems aim to guide the user to relevant items. Current recommender systems store user ratings on the server side. This way the scope of the recommendations is limited to this server only. In addition, the user entrusts the operator of the server with valuable information about his preferences.
Thus, we introduce the private, personal movie recommender OMORE, which learns the user model based on the user’s movie ratings. To preserve privacy, OMORE is implemented as Firefox add-on which stores the user ratings and the learned user model locally at the client side. Although OMORE uses the features from the movie pages on the IMDb site, it is not restricted to IMDb only. To enable cross-referencing between various movie sites such as IMDb,, Blockbuster, Netflix, Jinni, or Rotten Tomatoes we introduce the movie cross-reference database LiMo which contributes to the Linked Data cloud.


In the following, you can watch my presentation I prepared for the Semantic Web Challenge:


In the following, you can see a preview of the Semantic Web Challenge 2009 poster titled “OMORE”:
Poster of OMORE, a firefox plugin for online movie recommenations


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Personal Cross-Site Movie Recommender System Implemented as Mozilla Firefox Add-On

Online stores or Web page bring information about a myriad of items such as books, CDs, restaurants or movies at the user’s fingertips. Although, the Web reduces the barrier to the information, the user is overwhelmed by the number of available items. Therefore, online stores provide recommender systems that aim to guide the user to relevant items. However, recommender systems are generally limited to the Web page’s content and the explicit or implicit ratings provided by the users on the particular Web page. User are lazy when it comes to repeat providing rating information to recommender systems on other Web pages. That is a typical lock-in situation based on high transaction costs such that people are addicted to one or at least a limited number of Web pages.

People are required to have an account on a particular Web page before being provided with interesting recommendations. People may have concerns about providing explicit or implicit ratings on items that may expose some delicate details about their privacy. But many rather small online stores do not even provide recommendations.

Thus, we need a recommender system that (1) recognizes items over various Web pages as the same and remembers the ratings for those, (2) applies algorithms to provide recommendations and (3) smoothly integrates the rating and recommendation functionality directly in the Web site. We found the basic infrastructure for such a recommender system in the Firefox Add-on API and WEKA, a common data mining library.
We formulated these requirements as a master thesis. We were very happy to engage Tobias, an excellent master student.

The described recommender system implemented as Firefox Add-on can be downloaded at s.e.a.l. group site.


Online stores and Web portals bring information about a myriad of items such as books, CDs, restaurants or movies at the user’s fingertips. Although, the Web reduces the barrier to the information, the user is overwhelmed by the number of available items. Therefore, recommender systems aim to guide the user to relevant items. Current recommender systems store user ratings on the server side. This way the scope of the recommendations is limited to this server only. In addition, the user entrusts the operator of the server with valuable information about his preferences.

In this thesis, we introduce our recommender system OMORE, a private, personal movie recommender, which learns the user model based on the user’s movie ratings. To preserve privacy, OMORE is implemented as a Mozilla Firefox add-on, which stores the user’s ratings and the learned user model locally at the client side. Although OMORE makes use of the movie features, which are provided by the different movie pages on the, Blockbuster, Netflix and Rotten Tomatoes.

Tobias Bannwart: “OMORE – Private, Personal Movie Recommendations implemented in a Mozilla Firefox Add-on“, ed. by Amancio Bouza, Gerald Reif and Harald C. Gall, University of Zurich, July 2009. (master thesis)


Evaluation of the Adoption of New Features in a Web-Based Social Network

Together with Marc Vontobel’s main advisor Gerald Reif, I successfully advised and supported Marc with his bachelor thesis. He was my first student I advised at all. He reenginered Purple Leaf – a party portal – and investigated the impact of social relations among people with respect to acceptance rate of new features on a web page. At the time he finished with his thesis, the community of Purple Leaf consisted of several thousands of people.
It seems that one rather accepts and adopts a new feature when a friend already adopted it. It seems that the inhibition threshold is much lower due to the fact, that people trust their friends and thus, trust the feature and it added value. Marc did a great job that could not be expected from a Bachelor student, starting from the software engineering skills to the data gathering and complex Social Network Analysis (SNA). But he was already prepared from our precedent seminar on “Trust and Recommendation in Social Networks”.

We were surprised as he delivered not only his thesis but also a complete picture book with fantastic analysis of differenc aspects of his party community. He discovered the core group of party people being on most parties, the latent semantics among different music styles and drinks.


Purple Leaf is a social network which offers its member several possibilities to personalize its exclusive events by providing them unique online services. After the size of our platform suddenly increased from 300 initially invited guests to a multiple, we were obliged to completely revise the platform and enlarge our range of services. To embed these new services smoothly into the existing web presence, we fully restructured the application and changed the basis to a modern web framework. After that makeover, we designed five other services which we targeted to increase the customer loyalty and the entertainment value of our platform. Because new features are often not instantly accepted by existing users, we developed an integrated concept for boosting the acceptance of novel functionality. This concept is based on the technology acceptance model which was developed by Davis (1986). The model postulates that the actual use of a new feature is solely based on external factors. On the one hand, there are factors which influence the ‘perceived ease-of-use’ and on the other hand some that have impact on the ‘perceived usefulness’. In order to foster the perceived ease-of-use, we developed several usability concepts and tried to figure out how Web 2.0 features can help to simplify different processes. Beside the creation of intuitive user interfaces and plain procedures, we worked on an elaborated data and application structure which itself also contributed a big part to the simplicity of the new functionality. After we had embedded the services into our Internet portal, we started to analyze the acceptance of one new feature: ‘The most favored Guest’. This service allows every sign up member to define his personal list of favored guests for an upcoming event. Once the selected users are informed about their election, they, in turn, have the chance to define their own list. After a first round of selection, we tried to boost the personal acceptance of our members by providing specific incentives. Beside the active interventions into the process of adoption, we also analyzed a passive phenomenon: Does some kind of peer pressure exist within virtual cliques? If so, there might emerge some interesting changes in common marketing strategies which could narrow down the target audience to some single users of the network. In addition, we visualized some of the encountered situations and putted them together in an illustrated book as supplement to this paper.

Marc Vontobel: “Purple Leaf – Evaluation of the Adoption of New Features in a Web-Based Social Network”, ed. by Gerald Reif, Amancio Bouza, Harald C. Gall, University of Zurich, December 2008. (bachelorsthesis)

Graph-Based Knowledge Browser for Content Management Systems

A week ago, the 16th of May, I finished my master thesis about an implementation of a graph-based knowledge browser for a content management system (CMS). Now, I spend time in relaxing and organising my next steps to the future. The current IT market is asking for graduates and I remark it every time taking a look to my email account, if you know what I mean ;).

The time writing my master thesis was absolutely great. It was extremely work intensive, but great! I got a lot of support from my family and girlfriend, and from my friends too. Thank you at this point. Now, I know what it means to work from 7.30 to 23.00 over several months every day including the weekend. I experienced that working over 100 hours a week isn’t really efficient. You work not at 100% and your personal efficiency rate decreases every additional day. It’s not recommendable to work many over a long period of time. It does not only affect your work, if you know what I mean.

Anyhow, my thesis’s topic seems to be very attractive. During my research I got lots of requests from all over the world. A Professor from the St. Louis University in America was interested in using my tool for further research on Natural Language Processing (NLP). Other knowledge workers wanted to share experience. The results of my research and the potential of an interactive knowledge map for knowledge transfer leads me to possible future works. I just got some recommendations searching for venture capitalist to innovate my invention. We’ll see. It’s not the only project on my fingertips.


The success of knowledge transfer is crucial in the area of knowledge management. Not only companies in outsourcing-relations have the need of successful knowledge transfer. Organisations have the need of successful knowledge transfer too in order to create market advantages. This thesis introduces a graph-based knowledge browser for a CMS to support the topic of knowledge transfer by providing ?shared material? for generating knowledge and providing easy access to knowledge by visualising knowledge as associative networks. Knowledge is presented as graph or radial layout in hyperspace. Web 2.0 technologies like AJAX and SVG are used for the implementation.

Entering the Semi Finals of International User Interface Competition with a Knowledge-Graph Visualization

I’m proceeding to the next round in the Imagine Cup 2007 as 3 ranked team. Only 30 Teams with 1-2 persons had the chance to proceed to the next round. This 30 teams were elected by community voting. Only registered competitors were allowed to vote for other teams. No one could vote for his own team. The Imagine Cup consists of 7 categories and over 100′000 students from all around the world joined to compete.

Imagine the Wiki concept combined with Web 2.0 and let it become 2D. The knowledge of a Wiki or every other CMS is visualised as a topic map with nodes (e.g. article, person, knowledge entity, activity) and relations between them if they have a relation. You don’t see one article at once, you see the hole context of an article! You can directly add new articles in the topic map or knowledge browser and can directly paint relations between nodes. The topic map is rendered in hyperspace to focus on the nodes in the center of the screen. But you can use your mouse to move the hyperspace and the hole topic map (i.e. graph). The layout is calcualted in realtime with either a Spring model or a radial layout. In the spring model repulsive and attractive forces between nodes are calcualted to get a layout with minimum edge crossings etc. (graph layout heuristics). It looks really nice ; It runs on a Web browser and with Web 2.0 technologies (Ajax).

My mentor Benjamin promoted my currently successful participation in the Imagine Cup 2007 at the Department of Informatics at the University of Zurich. He published a news article about my current ranking (3rd rank) and proceeding to the semi finals:

Leaderboard of the Imagine Cup 2007. My team is called IfIface

Leaderboard of the Imagine Cup 2007. My team is called IfIface

IfI Student Enters Semi Finals in International User Interface Competition

IfI diploma student Amancio Bouza ranked 3rd in the user interface discipline to enter the semi-finals of Microsoft’s international computer science talent competition Imagine Cup. His successful contribution presents a novel AJAX powered user interface. The solution improves accessing and modifying graph based knowledge structures in an enterprise content management system. The user interface unites editing and browsing functions, and therefore will empower regular knowledge workers to view and change how knowledge is represented within their organization more easily.

The diploma thesis is currently under development with the Information Management Research Group at the IfI. Since Mr. Bouza seems to be the only Swiss participant in the competition, he hopefully will advance to the final round held this summer in Korea.

Published: 04.04.07


Knowledge Graph for the Exploration of the Wikipedia

Based on the graph-browser JSaurus, I implemented Wikigraph, a simple graph-based visualization of the content of Every node in the graph represents a topic. Topics are connected to each other if and only if one topic refers to the other one. The references are take from the meta tag keywords of the topic’s website.

But what is the advantage of the graph-browser Wikigraph? Well, first of all, it is possible to create a knowledge map of wikipedia‘s content. The knowledge map shows which topics are related to other topics. You have a breath overview about related topics. In other words you see the context of a selected topic.
As an example you can search for Informatics. As result you get Informatics and some linked topics (i.e., Mathematics, Information, Information System). You get the related topics to the related topics to. With all the relations you the context of the informatics.
The context can support you understanding a specific topic rather to read its content twice.

The main advantage is that you don’t have to find the right keyword to find the specific topic anymore. You search by context and not by keyword. You only have to search for a topic of the same context. You get a map of topics of the same context and you can selected the right one or browse further. So, Wikigraph provides not only searching by keyword, it provides searching by browsing too.

JSaurus – A Graph Visualization Framework in JavaScript

Jsaurus is a visualization tool to display a thesaurus with its nodes and relations in between. Jsaurus is written in JavaScript and DHTML. The goal of Jsaurus is to provide a piece of softare that manages every type of thesaurus and manages the visualization and behavior of nodes and relations too.
Jsaurus is build with the MVC design pattern. This pattern separates the model (data), the visualization and the control of the model from each other and defines interfaces to communicate between each layer. The advantages is the creation of more transparency and each layer can easy replaced by a new version or a complitely other one. In the Jsaurus case, the model is the thesaurus, the controller and eventhandler build the control layer and the visualization layer consists of a particle system and a renderer.

Below you can see an example of a thesaurus with 5 nodes and wihthout any relations. The particle system calculates the behavior of the nodes in the viszalization. The current particle system gives a kind of gravitation to each node. It calculates the force of gravitation and infers the velocity and position of each node. The example below shows remembers to a 3D planet system.

I’m developing Jsaurus for my diploma thesis about a Graph Based Knowledge Browser for a CMS. I’m looking forward to visualize knowledge maps for enterprises using Microsoft Sharepoint Portal Server. But I’m still in the beginning of my diploma thesis. It will end in 6 months from now on.

Successfull Presented in CASH Newspaper

Success of the biggest online student community of Switzerland

Success of the biggest online student community of Switzerland

An article of Andi Gredig about has been published in the 49th release of CASH, a Swiss economic newspaper. Although I’m not one of the founders, I’m on the picture (the 2nd person from right). The article is about the financial success of the biggest swiss student community
On the photo are from left to right: Gian Marco Laube, Adrian Bührer, Markus Okumus, Amancio Bouza (that’s me) and Frank Renold.