Abstract: The multilingual search for transliterated content technique described herein enables a user to submit a search query in both a native script and its foreign script (e.g., Roman script) transliteration and return relevant results in both the scripts while taking care of the spelling variations in transliterated forms. The technique crawls the World Wide Web for data in both the native script and foreign script transliterated forms of the data. It uses a transliteration engine to generate native script equivalents of the foreign script transliterated data and disambiguates the data in native script (whenever possible). The unique native script word forms are then used to jointly index the data in both the scripts. If the query is in native script, it is directly searched for in the index, otherwise the transliterated query is first converted into native script form(s) and then searched in the indexed database to retrieve and rank results in both the scripts.

Abstract: Application service requests received by an application hosting framework are automatically differentiated and categorized, and resource usage patterns associated with the requests are predicted. Resource usage data points are successively extracted from the hosting framework. Elements of an initial resource usage pattern matrix are computed from the data points. An estimate for the number of categories of requests is computed from the initial resource usage pattern matrix, where the requests in each category have similar resource usage patterns. Elements of a resource usage signature matrix and request categorization matrix are computed from the estimate for the number of categories of requests and the initial resource usage pattern matrix.

Abstract: Application service requests received by an application hosting framework are automatically differentiated and categorized, and resource usage patterns associated with the requests are predicted. Resource usage data points are successively extracted from the hosting framework. Elements of an initial resource usage pattern matrix are computed from the data points. An estimate for the number of categories of requests is computed from the initial resource usage pattern matrix, where the requests in each category have similar resource usage patterns. Elements of a resource usage signature matrix and request categorization matrix are computed from the estimate for the number of categories of requests and the initial resource usage pattern matrix.