Abstract: A system and method for managing reconciled textual descriptions based on merchant quality rating are provided. Merchants providing items to an electronic marketplace submit merchant values corresponding to textual descriptions of attributes of the item. A merchant value analyzer component processes multiple merchant descriptions to select a set of textual descriptions based on a comparison of the textual descriptions and merchant quality ratings. Additionally, a merchant quality analyzer component calculates updated merchant quality ratings based on the submitted merchant values.

Abstract: A system described herein includes a receiver component that receives a dataset that is stored in a computer-readable medium of a computing device, wherein the dataset includes a plurality of queries issued by users to a search engine and a plurality of search results selected by the users upon issuing the plurality of queries. A distribution determiner component determines click distributions over the search results selected by the users with respect to the plurality of queries. A labeler component labels at least two queries in the plurality of queries as being substantially similar to one another based at least in part upon the click distributions over the search results selected by the users with respect to the plurality of queries.

Abstract: Techniques and systems are disclosed providing improved ranking of results to an online search-based query. One or more user types are identified for a search-based query, which may correspond to a number of user relevant results and which ones are selected. A user profile can be determined for the respective user types for the search-based query, which may identify a proportion of the users that belong to that type, and how many results are relevant to that type. A set of relevant results can be identified for the respective user types for the query, based on a number of results used by the user type. An improved ranking of the results can be determined for the query, from the one or more sets of relevant results, based on the user profiles and a desired user satisfaction metric for a desired number of users.

Abstract: Computer-readable media and computerized methods for automatically organizing search results according to task groups are provided. The methods involve aggregating a gallery of entities (e.g., search queries that share a common categorization) into a query class and assigning a dictionary (e.g., list of terms that are drawn from various sources) to the query class. The task groups are identified from the list of terms within the dictionary. The process of identification includes analyzing patterns of user search behavior to select terms from the list of terms, which reflect popular user search intents, and ranking the selected terms based on predetermined parameters to produce an ordering. Based on the ordering, a set of the selected terms that are highest ranked are declared the task groups. The task groups are employed to arrange the search results on a UI display and to provide a consistent and intuitive format for refining a search.

Abstract: Systems and methodologies for improved query classification and processing are provided herein. As described herein, a query prediction model can be constructed from a set of training data (e.g., diagnostic data obtained from an automatic diagnostic system and/or other suitable data) using a machine learning-based technique. Subsequently upon receiving a query, a set of features corresponding to the query, such as the length and/or frequency of the query, unigram probabilities of respective words and/or groups of words in the query, presence of pre-designated words or phrases in the query, or the like, can be generated. The generated features can then be analyzed in combination with the query prediction model to classify the query by predicting whether the query is aimed at a head Uniform Resource Locator (URL) or a tail URL. Based on this prediction, an appropriate index or combination of indexes can be assigned to answer the query.

Abstract: Search relevance failures are diagnosed automatically. Users presented with unsatisfactory search results can report their dissatisfaction through various mechanisms. Dissatisfaction reports can trigger automatic investigation into the root cause of such dissatisfaction. Based on the identified root cause, a search engine can be modified to resolve the issue creating dissatisfaction thereby improving search engine quality.

Abstract: A system and method of creating domain knowledge-base models required for automated system management, wherein the method comprises defining data storage system designer specifications comprising input/output parameters; analyzing a runtime system performance log of a data storage system; identifying relationship functions between different ones of the input/output parameters; deriving knowledge-base models from the designer specifications, the runtime system performance log, and the relationship functions; refining the knowledge-base models at system runtime using newly monitored system performance logs; and improving the accuracy of the knowledge-base models by detecting incomplete designer specifications, wherein the knowledge-base models are preferably generated by data mining techniques.