Abstract: A framework may be used for identifying low-rate search bot traffic within query logs by capturing groups of distributed, coordinated search bots. Search log data may be input to a history-based anomaly detection engine to determine if query-click pairs associated with a query are suspicious in view of historical query-click pairs for the query. Users associated with suspicious query-click pairs may be input to a matrix-based bot detection engine to determine correlations between queries submitted by the users. Those users indicating strong correlations may be categorized as bots, whereas those who do not may be categorized as part of flash crowd traffic.

Abstract: In accordance with an embodiment of the disclosure, a method for forming submicron size nanostructures on a substrate surface includes contacting a substrate with a tip coated with an ink comprising a block copolymer matrix and a nanostructure precursor to form a printed feature comprising the block copolymer matrix and the nanostructure precursor on the substrate, and reducing the nanostructure precursor of the printed feature to form a nanostructure having a diameter (or line width) of less than 1 ?m.

Abstract: Assigning session identifications to log entries and generating anonymous log entries are provided. In order to balance users' privacy concerns with the need for analysis of the log entries to provide high quality search results, non-user-specific data fields, such as a user's location (e.g., city, state, and latitude/longitude) and connection speed, are inserted into the log entries, and user-specific data fields, such as the IP address and cookie identifications, are deleted from the log entries. In addition or alternatively, prior to anonymization of the log entries, session identifications are assigned to identified groups of log entries. The groups are identified based on factors such as the user's identification, the IP address, the time of search, and differences between the search terms used in the search queries.

Abstract: The disclosure relates to methods of printing indicia on a substrate using a tip array comprised of elastomeric, compressible polymers. The tip array can be prepared using conventional photolithographic methods and can be tailored to have any desired number and/or arrangement of tips. Numerous copies (e.g., greater than 15,000, or greater than 11 million) of a pattern can be made in a parallel fashion in as little as 40 minutes.

Abstract: Assigning session identifications to log entries and generating anonymous log entries are provided. In order to balance users' privacy concerns with the need for analysis of the log entries to provide high quality search results, non-user-specific data fields, such as a user's location (e.g., city, state, and latitude/longitude) and connection speed, are inserted into the log entries, and user-specific data fields, such as the IP address and cookie identifications, are deleted from the log entries. In addition or alternatively, prior to anonymization of the log entries, session identifications are assigned to identified groups of log entries. The groups are identified based on factors such as the user's identification, the IP address, the time of search, and differences between the search terms used in the search queries.

Abstract: A system for dynamically updating user accessible features of a software application on a client computer has a user interface, a local usage data file, and a data mining engine. The user interface is adapted to receive operator inputs. The local usage data file is adapted to store usage information corresponding to the operator inputs. The data mining engine is adapted to process the stored usage information and to generate local adjustments to a user interface of the software application based on the operator inputs. In one embodiment, a server is adapted to receive usage data from a plurality of application instances on a plurality of client computers and to generate global adjustments based on the received usage data. In one embodiment, the system has a merge feature adapted to blend and resolve conflicts between local and global adjustments to generate an interface adjustment for the user interface.

Abstract: A search authoring tool for mapping queries to assets for use in an information retrieval system has a query-to-asset mappings database, a search authoring engine, and a search evaluation engine. The query-to-asset mappings database is built from search author input and user mappings. The search authoring engine is adapted to receive operator input and to generate one or more new query-to-asset mappings based on the received operator input. The search evaluation engine is adapted to compare the one or more new query-to-asset mappings to the existing mappings to determine if the one or more new query-to-asset mappings will cause performance degradation of the information retrieval system.

Abstract: A search mechanism is evaluated or a relevance model checked using session level and result level diagnostics based on user behavior during a search session with respect to queries entered and user responses to result lists. Tracking occurs of when content desired by a user exists, but is not returned in a search result list when a query is made by the user with intent to find the desired content, when content desired by the user does not exist, when content desired by a user exists, but is not recognized by the user in a result list or is too low in a result list. A user's intent and search context is also taken into consideration when performing search mechanism diagnostics.

Abstract: The ranking quality of a ranked list may be evaluated. In an example embodiment, a method is implemented by a system to access log data, ascertain which entries of a ranked list are skipped, and determine a ranking quality metric from the skipped entries. More specifically, log data that reflects user interactions with a ranked list having multiple entries is accessed. The user interactions include at least indications of which of the multiple entries are selected entries. It is ascertained which entries of the multiple entries of the ranked list are skipped entries based on the selected entries. The ranking quality metric for the ranked list is determined responsive to the skipped entries.

Abstract: The subject invention leverages data logging of responses to diagnostic reports to provide data that can be mined for diagnostic report quality information. Instances of the subject invention provide an initial diagnostic report assessment means to facilitate review by an entity. The entity's responses to the sorted diagnostic reports are logged unobtrusively to create diagnostic report quality data. This data is then analyzed by an analysis means that can then adjust the assessment means to improve its performance. In this manner, the performance of the assessment means is increased while reducing the workload of the entity reviewing the diagnostic reports. Other instances of the subject invention facilitate to increase the performance of a diagnostic report generating means as well. Instances of the subject invention can also employ machine learning techniques to facilitate in analyzing the quality data and/or in assessing the diagnostic reports.

Abstract: Assigning session identifications to log entries and generating anonymous log entries are provided. In order to balance users' privacy concerns with the need for analysis of the log entries to provide high quality search results, non-user-specific data fields, such as a user's location (e.g., city, state, and latitude/longitude) and connection speed, are inserted into the log entries, and user-specific data fields, such as the IP address and cookie identifications, are deleted from the log entries. In addition or alternatively, prior to anonymization of the log entries, session identifications are assigned to identified groups of log entries. The groups are identified based on factors such as the user's identification, the IP address, the time of search, and differences between the search terms used in the search queries.

Abstract: A computer-implemented method includes training a data mining classification model to statistically account for query-to-asset associations. This data mining classification model can be utilized as a component of an information retrieval system.

Abstract: A search authoring tool for mapping queries to assets for use in an information retrieval system has a query-to-asset mappings database, a search authoring engine, and a search evaluation engine. The query-to-asset mappings database is built from search author input and user mappings. The search authoring engine is adapted to receive operator input and to generate one or more new query-to-asset mappings based on the received operator input. The search evaluation engine is adapted to compare the one or more new query-to-asset mappings to the existing mappings to determine if the one or more new query-to-asset mappings will cause performance degradation of the information retrieval system.

Abstract: A search mechanism is evaluated or a relevance model checked using session level and result level diagnostics based on user behavior during a search session with respect to queries entered and user responses to result lists. Tracking occurs of when content desired by a user exists, but is not returned in a search result list when a query is made by the user with intent to find the desired content, when content desired by the user does not exist, when content desired by a user exists, but is not recognized by the user in a result list or is too low in a result list. A user's intent and search context is also taken into consideration when performing search mechanism diagnostics.

Abstract: A system for dynamically updating user accessible features of a software application on a client computer has a user interface, a local usage data file, and a data mining engine. The user interface is adapted to receive operator inputs. The local usage data file is adapted to store usage information corresponding to the operator inputs. The data mining engine is adapted to process the stored usage information and to generate local adjustments to a user interface of the software application based on the operator inputs. In one embodiment, a server is adapted to receive usage data from a plurality of application instances on a plurality of client computers and to generate global adjustments based on the received usage data. In one embodiment, the system has a merge feature adapted to blend and resolve conflicts between local and global adjustments to generate an interface adjustment for the user interface.

Abstract: The subject invention leverages data logging of responses to diagnostic reports to provide data that can be mined for diagnostic report quality information. Instances of the subject invention provide an initial diagnostic report assessment means to facilitate review by an entity. The entity's responses to the sorted diagnostic reports are logged unobtrusively to create diagnostic report quality data. This data is then analyzed by an analysis means that can then adjust the assessment means to improve its performance. In this manner, the performance of the assessment means is increased while reducing the workload of the entity reviewing the diagnostic reports. Other instances of the subject invention facilitate to increase the performance of a diagnostic report generating means as well. Instances of the subject invention can also employ machine learning techniques to facilitate in analyzing the quality data and/or in assessing the diagnostic reports.

Abstract: The subject invention relates to systems and methods that automatically learn data relevance from past search activities and apply such learning to facilitate future search activities. In one aspect, an automated information retrieval system is provided. The system includes a learning component that analyzes stored information retrieval data to determine relevance patterns from past user information search activities. A search component employs the learning component to determine a subset of current search results based at least in part on the relevance patterns, wherein numerous variables can be processed in accordance with the learning component to efficiently generate focused, prioritized, and relevant search results.