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Network analysis, large graph mining, evolution of social networks
- In our recent work we found interesting and unintuitive patterns for time evolving networks,
which change some of the basic assumptions that were made in the past. The main objective of
observing the evolution patterns is to develop models that explain processes which govern
the network evolution. Such models can then be fitted to real networks, and used to generate
realistic graphs or give formal explanations about their properties. In addition, our work
has a wide range of applications: we can spot anomalous graphs and outliers, design better
graph sampling algorithms, forecast future graph structure and run simulations of network
- Another important aspect of this research is the study of ''local'' patterns and structures
of propagation in networks. We aim to identify building blocks of the networks and find the
patterns of influence that these block have on information or virus propagation over the
network. Our recent work included the study of the spread of influence in a large person-to-
person product recommendation network and its effect on purchases. We also model the
propagation of information on the blogosphere, and propose algorithms to efficiently find
influential nodes in the network.
- Questions I ask in my work:
- With Natasa Milic-Frayling from Microsoft Research and Marko Grobelnik from Jozef Stefan Institute we are working on a method for summarizing text documents by creating a semantic graph of the original document and identifying the substructure of such a graph that can be used to extract sentences for a document summary. We start with deep syntactic analysis of the text and, for each sentence, extract logical form triples, subject--predicate--object. We then apply cross-sentence pronoun resolution, co-reference resolution, and semantic normalization to refine the set of triples and merge them into a semantic graph. This procedure is applied to both documents and corresponding summary extracts. We train linear Support Vector Machine on the logical form triples to learn how to extract triples that belong to sentences in document summaries. The classifier is then used for automatic creation of document summaries of test data.
See our publications on this topic.
- I spent the summer of 2002 at Royal Holloway University of London, Department of computer science in a group of John Shawe-Taylor. We were working on text classification problem on very imbalanced training sets (small Reuters categories, having 10,000 negative training examples and only a few (10) positive training examples). We extended the notion of linear programming boosting to handle uneven datasets and extensively compared the performance of a number of different boosting strategies, concentrating on the problems posed by uneven datasets.
See the ICML 2003 paper: Publications.
- During the summer of 2001 I was at Microsoft Research working on WebTrails. Our application supports user in accessing pages that the user has seen during an ongoing search and navigation session. To support the user in accessing pages in the web navigation history. We introduced web-trails or sessions - each page is part of a trail.
We provided a search facility over the pages in web navigation history. It comprises the following features:
We also provided tool for supporting the current navigation/search session: for each page we create it's thumbnail and present a set of thumbnails to a user. This provides much easier navigation than standard Back/Forward buttons. User can look to a number of linear views of the navigation history: time ordered accumulation, unique page accessed, topology of navigated pages, time/content abstraction of navigation history.
- Search on color scheme of the page (user can choose from a more specific to more general color palette and specify colors for individual regions of page)
- Search by example. We abstract page color scheme and present a set of representative pages. User can browse the tree and get more and more specific about page layout.
- Search on page contents or annotations (link text, search query, page content)
- Search based on time the page was seen.
See WebTrails presentation slides.
- Real time stereoscopic computer vision: Detection of human bodies using a sequence of stereo images. Back in 1999 I got a Small vision System stereo camera from SRI and built a real time system for tracking people and determining their position in 3-D.
- Constraint Logic Programming. In high school I was playing with Constraint Logic Programming for Scheduling School Timetables. I developed a finite domain CLP library written in C++.