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It is well known that the use of a good Machine Transliteration system improves the retrieval performance of Cross-Language Information Retrieval (CLIR) systems when the query and document languages have different orthography and phonetic alphabets. However, the effectiveness of a Machine Transliteration system in CLIR is limited by its ability to produce… (More)
Search engines today offer a rich user experience, no longer restricted to "ten blue links". For example, the query "Canon EOS Digital Camera" returns a photo of the digital camera, and a list of suitable merchants and prices. Similar results are offered in other domains like food, entertainment, travel, etc. All these experiences are fueled by the… (More)
Concept taxonomies such as MeSH, the ACM Computing Classification System, and the NY Times Subject Headings are frequently used to help organize data. They typically consist of a set of concept names organized in a hierarchy. However, these names and structure are often not sufficient to fully capture the intended meaning of a taxonomy node, and… (More)
A typical collection of personal information contains many documents and mentions many concepts (e.g., person names, events, etc.). In this environment, associative browsing between these concepts and documents can be useful as a complement for search. Previous approaches in the area of semantic desktops aimed at addressing this task. However, they were not… (More)
Recent studies suggest that associative browsing can be beneficial for personal information access. Associative browsing is intuitive for the user and complements other methods of accessing personal information, such as keyword search. In our previous work, we proposed an associative browsing model of personal information in which users can navigate through… (More)
Working on machine learning, information extraction, and structured data in Rakesh Agrawal's group. Worked with Thorsten Brants and other members of the Machine Translation group at Google. Worked on language processing and learning for building text-to-speech systems.