Abstract: A computer-implemented service recommends digital works (and/or creators of works) to a user based on works currently or previously played or downloaded by the user on a player device or based on playlists stored on the player device. The works may be, for example, music files, video files, electronic books, or other digital content for playing by users. A user may thus obtain personalized recommendations that are based on works obtained from sources (web sites, physical CDs, etc.) that are independent of the recommendations system. In one embodiment, the service identifies pairs of works (and/or work creators) that are similar to each other by virtue of the relatively high frequency with which they co-occur on playlists or within play histories of users. The resulting mappings are used to provide recommendations to users.

Abstract: Disclosed are methods and apparatus for clustering news stories, which are to be presented over a computer network. In general, an incremental clustering system is configured to update a current set of news clusters with newly arrived news articles without having to recompute the clusters for the entire corpus, as well as form new clusters for recently generated news topics. In one embodiment, a plurality of news articles are initially obtained via the computer network, and the news articles are clustered into a plurality of initial clusters. For only news articles, including any unclustered news articles, that are less than a predetermined age limit, it is determined in an incremental clustering process whether to form one or more new clusters or assign to the initial clusters.

Abstract: Methods of managing data. A master catalog of properties may be generated. An object model catalog containing a plurality of object models may be generated, each object model including at least one property listed in the master catalog. A data set including a plurality of data objects may be defined, each data object an instantiation of a respective object model from the object model catalog. Data may be collected in accordance with the data set definition. Data collection may be performed, at least in part, by an automatic data collection system.

Abstract: According to one embodiment, an information processing apparatus includes a keyword display module, a selection module and an information-retrieval module. The keyword display module is configured to display at least two keywords. The selection module is configured to select a keyword from the at least two keywords displayed by the keyword display module. The information-retrieval module is configured to retrieve information by using the keyword selected by the selection module. The keyword display module is further configured to display one or more keywords belonging to a preset category, as at least one of the at least two keywords.

Abstract: An apparatus for generating a collection profile of a collection of different media data items has a feature extractor for extracting at least two different features describing a content of a media data item for a plurality of media data items of the collection, and a profile creator for creating the collection profile by combining the extracted features or weighted extracted features so that the collection profile represents a quantitative fingerprint of a content of the media data collection. This collection profile or music DNA can be used for transmitting information, which is based on this collection profile, to the entity itself or to a remote entity.

Abstract: A method (200) of identifying a principal document in a document set is provided. An exemplary method includes obtaining a document set comprising a plurality of documents (202) and grouping the plurality of documents into a plurality of clusters based, at least in part, on a textual similarity between each of the plurality of documents (204). The method also includes obtaining one or more descriptive terms corresponding to the plurality of documents, wherein the descriptive terms are terms within the plurality of documents that have been identified as being useful for discriminating between the clusters (206). The method also includes, for each cluster, identifying a subset of descriptive terms based, at least in part, on a prevalence of the descriptive terms within the documents of the cluster (208) and identifying the principal documents in the cluster based, at least in part, on a prevalence of the subset of descriptive terms within each of the documents in the cluster (210).

Abstract: A density-based data clustering method executed by a computer system is disclosed. The method includes a setup step, a clustering step, an expansion step and a termination step. The setup step sets a radius and a threshold value. The clustering step defines a single cluster on a plurality of data points of a data set, and provides and adds a plurality of first boundary marks to a seed list as seeds. The expansion step expands the cluster from each seed of the seed list, and provides and adds at least one second boundary mark to the seed list as seeds. The termination step determines whether each of the data points is clustered, wherein the clustering step is re-performed if the determination is negative.

Abstract: A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the type attribute.

Abstract: A server computer which determines the configuration of a file for configuring a plurality of virtual computers respectively is configured to comprise: an OS/AP file evaluation criteria table which stores evaluation criteria for judging whether to split and manage a file required for the configuration of the virtual computers; a user data evaluation criteria TBL; and a verification and splitting unit which judges whether the file conforms to the evaluation criteria, and determines a part of a file judged to conform to the evaluation criteria as a first file stored as an entity and determines the remaining part of the file as a second file for referencing an entity of a predetermined destination storage.

Abstract: A first cluster of web objects is identified from a click-through data structure. The click-through data structure can organize web objects into clusters based on query results of web objects selected by a user. Also, a second cluster of web objects can be identified from a metadata data structure. The metadata data structure can organize web objects into clusters based on metadata associated with the web objects. An output set of web objects is selected, in real time, from the identifier clusters.

Abstract: Included are a candidate extraction unit 61 that extracts, from a document formed by a group of character strings, a longest consecutive partial string common to one character string and the other character string as a candidate for an important word related to the one character string; a candidate integration unit 62 that selects a longest partial string of the candidate for the important word related to the one character string and extracted by the candidate extraction unit 61; and a group integration unit 63 that integrates a group of the longest partial string of each character string selected by the candidate integration unit 62, this group not forming a subset of a group of the other character string, thereby forming a group of the important word.

Abstract: A clustering method yields a searchable hierarchy to speed retrieval, and can function dynamically with a changing document population. Nodes of the hierarchy climb up and down the emerging hierarchy based on locally sensed information. Like previous ant clustering algorithms, the inventive process is dynamic, decentralized, and anytime. Unlike them, it yields a hierarchical structure. For simplicity, and reflecting our initial application in the domain of textual information, the items being clustered are documents, but the principles may be applied to any collection of data items.

Abstract: A computer implemented method, apparatus, and computer usable program product for ranking and categorizing criminal offenders in a jurisdiction. In one embodiment, external data associated with the offenders is processed in a set of data models to generate a ranking index of criminal offenders. The external data comprises offender data elements related to prior arrests. The computer software and web application enables officers, detectives, and supervisors to research the offenders in their jurisdiction. They can intentionally track and monitor the status of the offenders that are not currently incarcerated. They can deliberately increase lawful contacts with these high-rate and treacherous offenders.

Abstract: Systems and techniques by which tables can be joined in a mapreduce procedure. In some implementations, when a large table of business data (e.g., having one billion transaction records or more) is to be joined with a large table of customer data (e.g., having hundreds of millions of customer records), then these two tables can be organized before the mapreduce procedure to speed up the table join. For example, the business data and the customer data can both be hash partitioned, based on the same key, into shards of business data and shards of customer data, respectively. The number of shards in these two groups has an integer relationship with each other: for example such that there are two business data shards for every customer data shard, or vice versa.

Abstract: Methods and apparatus for classifying data for use in data fusion processes are disclosed. An example method of classifying data selectively groups nodes of a classification tree so that each node is assigned to only one of a plurality of groups and so that at least one of the groups includes at least two of the nodes. Data is classified based on the classification tree and the selective grouping of the nodes, and the results displayed.

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: A data collection method for a process margin monitoring system of industrial equipment includes preparing a learning data set based on data determined to be normal in an operation history of the industrial equipment so that the learning data set is sorted for each operation mode, in a case in which the industrial equipment includes equipment units performing the same functions, receiving data for each of the equipment units and processing the received data as data for the equipment units, sorting and grouping associated ones of the data in the learning data set, and sampling the collected data to reduce the amount of data.

Abstract: Disclosed is a data processing device including a data acquisition unit for acquiring data from a medium, an integrated database for integrating the data acquired by the data acquisition unit thereinto, a data analysis determination unit for analyzing the data integrated into the integrated database, a display control unit for creating an image of a side view of and an image of a bottom view of a solid expressing the data integrated into the integrated database on the basis of an analysis result acquired by the data analysis determination unit and the data, and a display unit for displaying the images created by the display control unit.

Abstract: A computer-based method for character string matching of a candidate character string with a plurality of character string records stored in a database is described. The method includes performing a clustering operation on at least a portion of the plurality of character string records, the clustering operation generating a plurality of clusters, each cluster comprising a plurality of character strings from the plurality of character string records, the plurality of character strings in each cluster are determined to be similar with respect to each other based on at least one characteristic of the plurality of character strings. The method also includes generating a set of reference character strings that are selected from the plurality of character strings in each cluster, generating an n-gram representation for one of the reference character strings in the set of reference character strings, and generating an n-gram representation for the candidate character string.

Abstract: In one implementation, a method includes receiving a request for translation of one or more first keywords from a source language to a target language; and translating, using a machine translation process, the first keywords from the source language into a plurality of second keywords in the target language. The method can also include determining, by a computer system, frequencies with which each of the second keywords occur in a corpus associated with the target language. The method can further include selecting, by the computer system, a subset of the second keywords to use in the target language based on the determined frequencies of occurrence.

Abstract: A classification process may reduce the computational resources and time required to collect and classify training data utilized to enable a user to effectively access online information. According to some implementations, training data is established by defining one or more seed queries and query patterns. A bi-partite graph may be constructed using the seed query and query pattern information. A traversal of the bi-partite graph can be performed to expand the training data to encompass sufficient data to perform classification of the present search task.

Abstract: A computer-implemented method for processing electronic documents having different native file formats is provided. The method is implemented in a computer system comprising one or more processors configured to execute one or more computer program modules. The method includes (a) receiving electronic documents in different native file formats; (b) identifying the native file format for each received electronic document; (c) retrieving a stored configuration data for the identified native file format, the configuration data includes a mapping of regions of interest in the electronic document with the identified native file format and their associations with output fields; and (d) processing the electronic documents using their retrieved configuration data to extract data from the electronic documents.

Abstract: A method for generating event compilations during an event comprising: providing an event client designated to display event content captured at the event; identifying an event moderator to review event content captured by attendees of the event; receiving event content captured by one or more event attendees; transmitting the event content to the event moderator for review; receiving a response from the event moderator, the response indicating whether the event content is allowed or blocked; and displaying the event content from the event client at the event if the response from the moderator indicates that the event content is allowed.

Abstract: Disclosed is an information recommendation method for providing a construction method for a classified word database capable of rapidly accommodating changes in associations between words. The disclosed information recommendation method basically is based on the finding that, by analyzing occurrence frequency information of an arbitrary word in a Web site having an arbitrary classified word in real-time and obtaining the real-time degree of similarity between the classified word and the arbitrary word, it is possible to construct a database that is capable of being sensitive in responding to changes in associations between words.

Abstract: A process for reading entries in a directory is initiated. A first index is maintained to indicate how far the read has progressed in the directory. If, during execution of the process, the directory is partitioned into subdirectories, then a second index is maintained for each of the subdirectories to indicate how far the read has progressed in each of the subdirectories. A third index that indicates how far the read has progressed in the partitioned directory is also maintained.

Abstract: Methods, systems, and apparatuses, including computer programs encoded on computer-readable media, for aggregating conversion paths utilizing user interaction grouping. In one aspect, information regarding a plurality of conversion paths is received. Each conversion path includes one or more user interactions that include a plurality of dimensional data. A sorted list of grouping definitions that includes one or more group rules is received and the conversion paths are converted into group paths based upon the one or more group rules. Each group path includes one or more group elements corresponding to each user interaction of a corresponding conversion path. The plurality of group paths are aggregated based upon the number and order of group elements within each group path. Information regarding the aggregated group paths can then be provided, for example, through a report.

Abstract: An online service provider (OSP) operates online data centers to store members' data objects relating to various online member services of the OSP. An aggregated catalog lists members' data objects residing in the online data centers and also those residing in member computers' local storage. An aggregator monitors contents of the online storage facilities to detect new storage of prescribed types of data objects owned by the members, and also communicates with member computers to identify prescribed types of data objects newly stored in the respective local storage. The aggregator updates the aggregated catalog to list the newly stored data objects. Responsive to a request by a member, a finder searches the aggregated catalog and utilizes results of the search to provide, for display at the requesting member's computer, a consolidated listing of online data objects and locally stored data objects owned by the requesting member.

Abstract: Methods and systems for relating breaking news stories across content providers include receiving a breaking news headline for a breaking news from a content provider. The breaking news headline is tokenized in substantial real time by identifying a plurality of headline tokens. A plurality of news stories is received from a plurality of content providers. Each of the plurality of news stories is tokenized to identify a plurality of story tokens. The plurality of headline tokens and story tokens are analyzed to determine if one or more of the news stories are related to the breaking news headline. Based on the analysis, one or more of the news stories are mapped to the breaking news headline. The mapping enables presentation of the one or more news stories from one or more of the content providers while rendering the breaking news headline.

Abstract: A computer implemented method for clustering customers includes receiving a source set of customer records, wherein each customer record represents one customer, and each customer record includes at least one data attribute, and each data attribute has an attribute value; pre-processing the source set of customer records to generate a pre-processed set of customer records; executing a clustering algorithm on the pre-processed set of customer records to group the pre-processed set of customer records into clusters of a pre-defined number. The pre-processing comprises: determining the type of a customer in the source set of customer records; using a type attribute value to indicate the type of the customer in its customer record; normalizing data attribute values and type attribute values; weighting to the data attribute values and the type attribute values respectively to obtain weighted attribute values of the data attribute and weighted attribute values of the tune attribute.

Abstract: The disclosed embodiment relates to identifying performance regions in time-series data. An exemplary method comprises identifying, with a computing device, one or more streaks in the time-series data based on at least one streak parameter, ranking, with a computing device, the identified streaks based on at least one characteristic of the identified streaks, and predicting, with a computing device, a future occurrence of at least one streak based on the characteristics of the identified streaks. The steps of identifying and ranking may be carried out using at least one of a linear graph method, a statistical based approach, a curve-line intersection method, and a hypothesis-based method, and the step of predicting the future occurrence of at least one streak may comprise predicting at least one of how long a current streak will continue, when a current streak will end, and when a new streak will begin.

Abstract: Methods, systems, and techniques for cluster-based content recommendation are described. Some embodiments provide a content recommendation system (“CRS”) configured to recommend news stories about events or occurrences. In some embodiments, a news story about an event includes multiple related content items that each include an account of the event and that each reference one or more entities or categories that are represented by the CRS. In one embodiment, the CRS identifies news stories by generating clusters of related content items. Then, in response to a received query that indicates a keyterm, entity, or category, the CRS determines and provides indications of one or more news stories that are relevant to the received query. In some embodiments, at least some of these techniques are employed to implement a news story recommendation facility in an online news service.

Abstract: A computer-executed method for grouping data comprising, with a processor, generating a number of sorted runs from an unsorted input, storing the sorted runs in temporary storage, placing pages of data from the sorted runs, one at a time, into a portion of a buffer allocated to receive that page, and from the allocated portion of the buffer, merging each page of data, one at a time, into a number of aggregated records, the number of aggregated records also being stored in the buffer.

Abstract: A computer-based method is described for categorizing inventions within the context of an invention landscape. A set of key phases and/or semantic properties is employed based upon the likelihood that the description of the invention to be categorized will share these key phrases and/or semantic properties with the descriptions of similar inventions from within the invention landscape. The results are ranked in such a way as to enable a tentative assignment of the target invention to one or more categories, and to optionally estimate the value of the invention.

Abstract: A computer executed method of exploiting correlations between original and desired data sequences during run generation comprises, with a processor, adding a number of data values from a data source to a first memory device, the first memory device defining a workspace, determining whether the data values within the workspace should be output in ascending or descending order for a number of runs, and writing a number of the data values as a run to a second memory device in the determined order.

Abstract: A system and method for processing an SQL query made against a relational database is disclosed. In one example embodiment, the method includes receiving the SQL query made against the relational database. Further, the received SQL query is parsed to obtain each operator and associated one or more operands and sequence of execution of the operators. Furthermore, a closure-friendly operator is dynamically generated for each operator and the associated one or more operands in the received SQL query. In addition, the dynamically generated closure-friendly operators are executed based on the obtained sequence of execution of the operators.

Abstract: An apparatus is provided that includes a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least perform a number of functions. The apparatus is caused to direct presentation of a list for a plurality of patients and that is clustered by patient. The apparatus is caused to apply a keyword filter to identify a subset of the patient exams that match the keyword filter, and rank the respective exams by relevance to the keyword filter. The apparatus is caused to direct presentation of a filtered list of patient exams that is clustered by patient in the filtered list of patient exams. And for each patient having patient exams in the subset of the patient exams, the respective patient exams are in ranked order in the filtered list of patient exams according to the keyword filter.

Abstract: Techniques and tools are described for refining source-code query results. For example, source-code query results for a query can be generated, semantic clusters of the source-code query results can be generated, and based on a selection of a semantic cluster option, refined source-code query results can be sent. Also, for example, source-code query results can be received, selections of facet values associated with groups of the source-code query results can be sent, and based on selected facet values, a subset of the source-code query results can be received.

Abstract: A computer-based method is described for categorizing inventions within the context of an invention landscape. A set of key phases is employed based upon the likelihood that the description of the invention to be categorized will share these key phrases with the descriptions of similar inventions from within the invention landscape. The results are ranked in such a way as to enable a tentative assignment of the target invention to one or more categories, and to optionally estimate the value of the invention.

Abstract: An information processing apparatus includes: a document analyzing unit that extracts phrases including a pair of entities, to which a relevance label is granted, from document data; and a label granting unit that grants the relevance label. The label granting unit acquires vocabulary syntax patterns included in the phrases including the pair of entities, acquires the appearing number of times the vocabulary syntax pattern appears in the document data from the document data, counts the number of pairs of entities, sets a probability model created from a probability density distribution, a parameter Z indicating validity of the granting of the relevance label, and a parameter a indicating a probability of rightly granting the relevance label, calculates the parameters Z and a for which a likelihood is maximum in the probability model, evaluates the validity of the granting of the relevance label, and grants the relevance label on the evaluation result.

Abstract: A data size characteristic of contents of a related unit of data to be written to a storage by an input/output module of a data storage application can be determined, and a storage page size consistent with the data size can be selected from a plurality of storage page sizes. The related unit of data can be assigned to a storage page having the selected storage page size, and the storage page can be passed to the input/output module so that the input/output module physically clusters the contents of the related unit of data when the input/output module writes the contents of the related unit of data to the storage. Related methods, systems, and articles of manufacture are also disclosed.

Abstract: In a generation device, a term determiner, for reference terms and a similar meaning term that has similar meaning to any of the reference terms, determines if each of the reference terms and the similar meaning term are both included in a document data group. An extractor extracts a reference term and the similar meaning term of the reference term that were both determined to be included in the document data group. A priority determiner determines an output priority to the extracted similar meaning term on the basis of appearance of at least either of the similar meaning term and the reference term in the document data group. And a list generator generates a the similar meaning term list in such a way that the extracted reference term, the similar meaning term of the extracted reference term, and the output priority are associated with one another.

Abstract: The present invention provides a method and system for automatic objects classification. The method comprises: acquiring a set of objects; classifying the objects based on query log to generate a first classification result; classifying the objects based on ontological information to generate a second classification result; and semantically fusing the first and second classification results to generate a final classification result. According to the present invention, compared with the prior arts, by semantically fusing the query log-based classification result and the ontology-based classification result, the accuracy and user-friendness of the object classification can be improved.

Abstract: Unsupervised clustering can be used for organization of micro-blog or other short length messages into message clusters. Messages can be compared with existing clusters to determine a similarity score. If at least one similarity score is greater than a threshold value, a message can be added to an existing message cluster. If a message is not similar to an existing cluster, the message can be compared against criteria for starting a new message cluster.

Abstract: A tied server includes a first storage unit that stores appearance patterns of messages having a transaction identifier to identify a transaction. The tied server also includes a second storage unit that stores messages executed on the transaction DB server having the transaction ID by the application server and communicated between an application server and a DB server. The tied server classifies the messages stored in the second storage unit with respect to each transaction based on the appearance patterns of the messages stored in the first storage unit.

Abstract: A category classification processing device includes a search unit that stores, as a search keyword log assembly, Q&A examples, which are actually referred to by a client, together with keywords; and a category extracting unit that obtains keyword storage frequencies expressing a number of times each of the keywords, which are recorded together with the Q&A examples in the search keyword logs, is stored for each of the Q&A examples, extracts, as category candidates of each of the Q&A examples, an m number of top keywords (m being a positive integer) in a descending order of the keyword storage frequency, uses the extracted category candidates as categories, and associates the categories with the Q&A examples.

Abstract: Files can be segmented into distinct groups and allocated storage units such as blocks. Files associated with parent and child files can be segmented into separate groups, for instance. Further, a group associated with parent files can be extended to include additional blocks reserved for subsequent update. Additionally, metadata can be merged across groups to provide a unified view of the distinct groups.

Abstract: Architecture for completing search queries by using artificial intelligence based schemes to infer search intentions of users. Partial queries are completed dynamically in real time. Additionally, search aliasing can also be employed. Custom tuning can be performed based on at least query inputs in the form of text, graffiti, images, handwriting, voice, audio, and video signals. Natural language processing occurs, along with handwriting recognition and slang recognition. The system includes a classifier that receives a partial query as input, accesses a query database based on contents of the query input, and infers an intended search goal from query information stored on the query database. A query formulation engine receives search information associated with the intended search goal and generates a completed formal query for execution.

Abstract: An indexing database utilizes a non-transitory storage medium. A pattern matching processing unit generates preclassification data for the network data packets utilizing pattern matching analysis. At least one processing unit implements a storage process that receives the network data packets, stores the network data packets in at least one of the slots, and transfers the network data packets to a packet capture repository when slots in a shared memory are full. A preclassification process requests from the pattern matching processing unit the preclassification data. An indexing process determines, based upon the preclassification data, whether to invoke or omit additional analysis of the network data packets, and performs at least one of aggregation, classification, or annotation of the network data packets in the shared memory to maintain one or more indices in the indexing database.

Abstract: A content data management apparatus that manages tag data indicating attributes relating to content data, comprising: an extraction section that extracts positional information indicating geographic positions associated with the content data and time information indicating time points associated with the content data, the positional information and the time information being attached to the content data; a speed computation section that computes speeds associated with the content data, based on the positional information and the time information extracted by the extraction section; and a grouping section that groups the content data, based on the speeds computed by the speed computation section.

Abstract: Determining one or more preferred categories for a user is disclosed, including: determining a plurality of access attribute values corresponding to a plurality of types of access attributes associated with an access of the website by the current user; determining a plurality of categories corresponding to the plurality of access attribute values based at least in part on stored corresponding relationships between categories and access attribute values, wherein at least a portion of the determined plurality of categories comprises one or more preferred categories from which one or more products are configured to be recommended to the current user; and presenting product information associated with the one or more preferred categories.