Difference between revisions of "Social Software and Semantic Web"

Title: Facebook Automatic List Suggestion
Description: In Facebook each user can create lists of friends (for example: "high school","university","tennis") to better filter information and manage privacy. Goal of this project is to develop a Facebook application to analyze a user's network of friends and automatically detect groups to suggest lists.
Tutor: DavidLaniado, RiccardoTasso
Additional Info: CFU 5 - 10 / Bachelor of Science, Master of Science / Course

Title: Social Network Data Extraction From Online Communities
Description: With the growth of the Web and the emergence of online communities, a huge amount of data regarding social relationships is now available, that was unthinkable until a few years ago. The network of connections may unveil precious information about communities structures and dynamics and the spreading of information in the Web. Aim of this project is to design and develop a software tool to extract this kind of information from a single social network platform (decided by the student). It may be required also some kind of analysis or visual representation of the collected data.
Tutor: DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: Wikipedia Page Social Network
Description: Goal of this project is to study the social network of Wikipedia pages, where two pages are connected if they share at least one main contributor. This social network can be studied to reveal interesting information; for example, it is possible to extract clusters of pages which apparently have nothing in common. A metric of distance between pages in the network can be defined, and compared with other metrics, such as the distance in the category tree or in the hyperlink graph.
Tutor: DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: Wikipedia Tripartite Graph
Description: When a user edits a Wikipedia page, we can establish a link among her, the page and the categories to which the page belongs. A model to represent this information is a tripartite graph. Aim of this project is to build a tripartite graph from Wikipedia users, pages and categories, and mine the outcome network to extract emergent semantics.
Tutor: DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 20 - 20 / Master of Science / Thesis

Title: Wikipedia category map
Description: Wikipedia articles are organized in a hierarchy of categories, manually assigned by users. This process can be considered a huge effort for the collective categorization of human knowledge; the result is a wide and disordered graph which can provide precious information for a variety of applications (natural language processing, information retrieval, ontology building...). In the project "Wikipedia Category Map" a tool has been developed to extract the graph of Wikipedia categories, to store it in RDF format and to interactively visualize and explore it. Aim of this project is to analyze the resulting graph for the extraction of semantic relationships; for example it is possible to define metrics of distance between topics in the graph, which can be useful for various purposes in information retrieval.
Tutor: DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: Wikipedia Tripartite Graph
Description: When a user edits a Wikipedia page, we can establish a link among her, the page and the categories to which the page belongs. A model to represent this information is a tripartite graph. Aim of this project is to build a tripartite graph from Wikipedia users, pages and categories, and mine the outcome network to extract emergent semantics.
Tutor: DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 20 - 20 / Master of Science / Thesis

Title: Extending a search engine with semantic information
Description: We are used to keyword-based search engines, where only documents matching the exact words in the query are retrieved. In a traditional search engine, if you submit the query "a dinosaur in a university in Lombardy" you won't probably find a document containing the phrase "a velociraptor in Politecnico di Milano", even though it's more or less what you were looking for.

Aim of this project is to expand a traditional search engine with semantic information, so that also documents containing words related to the ones in the query can be retrieved. Existing thesauri and ontologies can be used, as well as more dynamic and collaborative sources of knowledge such as user tags and wikipedia pages and categories.

Starting points for this work can be the projects "SeQuEx - Semantic Query Expansion" and "Enriching search results with semantic metadata".
Tutor: DavidLaniado, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: A Firefox extension for semantic annotations
Description: Aim of this project is to develop a Firefox extension, to allow a community of users to annotate resources on the Web using a shared RDF vocabulary. While browsing the Web, a user should be able to visualize the annotations relative to the page they are visiting, and to add new annotations as well.
Tutor: DavidLaniado, DavideEynard, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: Annotation aggregators from social applications
Description: Annotations are metadata published about a resource, such as tags in del.icio.us, comments on stumbleupon.com, or twines on Twine.com. One of the main problems of these annotations is that they are not expressed in a standard format: thus, any tool trying to aggregate information from these sources should be able to access each one of them in a different way. The purpose of this project is to develop translation tools for different social annotation systems, collect their data in a common format (expressed using an ontology), and show them through a unique user interface, able to display different annotations (i.e. geo coordinates, dates, tags, etc.) in different ways. Moreover, tests and evaluations should be performed on this aggregator to show how efficient the queries are when performed on-the-fly or from an intermediate knowledge base.
Tutor: DavideEynard, DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Bachelor of Science, Master of Science / Course, Thesis

Title: Detecting patterns in ontology usage
Description: When building a new knowledge base the reuse of existing, well known vocabularies is often desirable. However, sometimes it is not clear which ontology should be preferable or which term is best suited for a specific application. Aim of this project is to detect patterns in ontology usage by harvesting ontologies which use a given schema (i.e. Foaf or Dublin Core) and analysing how people are using them in practice. The resulting application should download ontologies from the main semantic search engines (such as http://watson.kmi.open.ac.uk/ and http://sindice.com/), parse them and calculate statistics about the terms used inside them. The tool should show these statistics, save them in an appropriate format and make them available through an API for use by external applications.
Tutor: DavideEynard, DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 20 / Master of Science / Course, Thesis

Title: Use case design and implementation for semantic annotation
Description: Semantic annotations offer a variety of possibilities to enhance the user experience while browsing the Web. Aim of this project is to propose one scenario in which their usefulness is exploited for a specific community of users. In detail the project requires to design a simple ontology which describes some kind of domain to annotate resources on the Web and implement an interface to query it and insert assertions inside a semantic store (through SPARQL).

One possible example is the annotation of mp3 files available on the Web. They can be classified in genres or associated to datatype properties, such as rating, title, length and release date... also exploiting data already available in http://musicbrainz.org/
Tutor: DavideEynard, DavidLaniado, RiccardoTasso, MarcoColombetti
Additional Info: CFU 5 - 10 / Bachelor of Science, Master of Science / Course, Thesis