Alexandros Ntoulas is Researcher at Microsoft Research in Mountain View, California, where he is working on integrated search of structured and unstructured data and entity extraction. He received a Ph.D. degree in Computer Science from the University of California Los Angeles (UCLA) in 2006 and a B.Sc. from the Computer Engineering and Informatics Department (CEID) of Patras University, Greece in 2000. His area of expertise is Databases and Web information systems and his research interests are in the study of systems and algorithms that facilitate the monitoring, collection, management, mining and searching of information on the World Wide Web. He publishes research papers in international conference proceedings and journals and has three patents pending. He is the co-founder of Infocious (now Lingo Semantics), a Web Search Engine that applies linguistic analysis techniques in order to provide highly relevant results and a better search experience to the user. He is the recipient of the Best Paper Award for the ICDE 2005 conference.

• Ph.D. Computer Science Department, University of California Los Angeles (UCLA), 2006.
  Advisor: Professor Junghoo "John" Cho.
  Dissertation Title: Crawling and Searching the Hidden Web.
  
  
  
• M.Sc. Computer Science Department, University of California Los Angeles (UCLA), 2003.
  Advisor: Professor Junghoo "John" Cho.
  
  
  
• M.Sc. Computer Engineering and Informatics Department, Patras University, 2003.
  Advisor: Professor Dimitris Christodoulakis
  Thesis Title: Automatic Web Directory Construction.
  
  
  
• B.Sc. Computer Engineering and Informatics Department, University of Patras, 2000.
  Advisor: Professor Dimitris Christodoulakis
  Thesis Title: A System for Managing and Querying Corpora.
  

The Web has brought together a wide variety of digital information into publicly accessible media. However, because of the sheer quantity and varying quality of available information, the user often feels overwhelmed and disoriented during his pursuit of information. My research focuses on the monitoring, collection, sharing, mining and searching of information in order to help the users identify and extract the desired information quickly and effectively through simple and intuitive methods.

Here is a list of the projects that I have worked on:

• Hidden-Web Crawling: Search engines employ automated programs called crawlers to download pages from the Web. Typical crawlers today follow links from one Web page to another and download every page in their path. However, an ever-increasing amount of information on the Web is accessible only through search interfaces; such information is called the Hidden or Deep Web. For example, in PubMed (www.pubmed.org) users can access pages of high-quality papers on medical research only after issuing a set of keywords. Since there are no static links to the Hidden-Web pages, current search engines cannot index them, thus depriving users from accessing potentially valuable information. In my research, I studied how we can build an effective Hidden-Web crawler that can autonomously discover and download pages from the Hidden Web.
  [ JCDL 2005 | extended version | slides ]

• Indexing Optimizations: Search engines typically create and maintain large-scale indexes that are used to answer thousands of user queries per second. Given the vast amount of information available on the Web, such indexes can easily grow very large and become very costly to operate. In my research, I proposed and evaluated algorithms for reducing the size of an index, without sacrificing the quality of results that we return to the users.
  [ SIGIR 2007 | slides ]

• Web Spam Detection: One of the most important goals of Web search engines is to return highly relevant results to the users. However, given the potential monetary value of the traffic that search engines direct to Web sites, some Web site operators craft spam Web pages that are useless to human users and exist for the sole purpose of fooling the search engine rankings into returning such pages, in the hope of attracting traffic. At Microsoft Research, we studied the characteristics of Web spam and proposed fast and highly accurate algorithms for removing spam from the search engine results.
  [ WWW 2006 | slides ]

• Data Synchronization: Information on the Web is constantly updated. Therefore, once the search engine’s crawler has downloaded pages and stored them locally, the crawler has to refresh the pages periodically. In my research, I performed large-scale experimental studies on several million pages collected weekly from the Web over a period of one year. We induced models that capture the evolution of Web sites and Web-accessible textual databases. The models were then used to predict when we should refresh the Web pages. Additionally, since the enormous size of the Web limits most crawlers to downloading only a subset of the entire Web, I studied sampling-based algorithms for determining which subset of the Web the crawler should focus on.
  [ VLDB 2002 , slides | WWW 2004 , slides | ICDE 2005 , slides ]

• The Infocious Web Search Engine: As part of my research, I worked on the implementation of a full-fledged commercial Web search engine called Infocious, which blends my research in crawling, data synchronization and indexing along with a variety of natural language processing (NLP) techniques in order to improve the quality of results presented to the users. The search engine performes highly efficient crawling and indexing of Web data, operates in a distributed fashion over a cluster of commodity machines, provides failover capabilities that guarantee 24/7 availability of the service, and gracefully scales to the size of the Web, currently indexing more than 2 billion pages.
  [ WWW 2005 | slides ]

• Automatic Web Directory Construction: Web Directories provide an alternative (to search engines) way of locating relevant information on the Web. Typically, Web Directories rely on humans putting in significant time and effort into finding important pages on the Web and categorizing them in the Directory. I studied ways for automating the creation of a Web Directory by assigning every page from a given collection of pages to a given subject hierarchy. Our method is based on the identification of important sequences of terms within Web pages (called lexical chains), which are then used to assign the pages to categories in the hierarchy.
  [ APWeb 2006 ]

• Co-chair, Special Session on Web Search and Mining (PCI 2007)
• Editorial board, Data Mining with Ontologies: Implementations, Findings and Frameworks. Book published by the Idea Group Inc., 2007
• Program Committee, ACM International Workshop on Web Information and Data Management (WIDM 2007)
• Program Committee, Workshop on Improving Web retrieval for non-English queries (SIGIR 2007)
• Program Committee, Poster Session, World Wide Web Conference (WWW 2006)
• Program Committee, ACM Hypertext 2005 Workshop on Peer to Peer and Service Oriented Hypermedia (HT 2005)
• Program Committee, Poster Session, World Wide Web Conference (WWW 2005)
• Referee, World Wide Web Conference (WWW 2007)
• Referee, International Conference on Knowledge Discovery and Data Mining (KDD 2007)
• Referee, International Conference on Management of Data (SIGMOD 2006)
• Referee, ACM Hypertext Conference (HT 2005)
• Referee, International Conference on Very Large Databases (VLDB 2005)
• Referee, International Workshop on the Web and Databases (WebDB 2005)
• Referee, Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD 2004)
• Referee, International Conference on Conceptual Modeling (ER 2004)
• Referee, ACM Conference on Information and Knowledge Management (CIKM 2004)
• Referee, International Workshop on the Web and Databases (WebDB 2004)
• Referee, World Wide Web Conference (WWW 2004)
• Referee, International Conference on Management of Data (SIGMOD 2003)
• Referee, Student Research Workshop, Association of Computational Lingustics (ACL 2002)
• Referee, International Journal on Artificial Intelligence Tools (IJAIT)
• Referee, Data Mining and Knowledge Discovery Journal (DMKD)
• Referee, IEEE Transactions on Knowledge and Data Engineering (TKDE)

• Mailing Address:
  
  Alexandros Ntoulas
  Microsoft Search Labs
  SVC 5/2224
  1065 La Avenida
  Mountain View, CA 94043, USA
  
  
• Email: ntoulas@cs.ucla.edu
  
• Office Phone: +1 (650) 693 2187
  
• Office Fax: +1 (650) 693 3329