Abstract: Methods, systems, and computer programs are presented for obtaining histogram data from a database utilizing an interface with histogram-related options. One method includes an operation for providing, by a server, an application programming interface (API), to access the database, which includes a histogram request, to obtain histogram data from the database, with histogram options. The server receives, from a client device, a first histogram request including histogram options. Additionally, the method includes an operation for identifying bins for the histogram based on the one or more histogram options. For each bin, the server accesses the database to obtain data for each bin. The server returns, to the client device, the histogram data for the histogram as a table containing bin values for all the bins, where the client device is configured to present the histogram to a user based on the histogram data.

Abstract: The present disclosure, in some embodiments, describes a system for classifying members of a collection of texts into clusters to generate merged data collections. A member text can range from a single document to the contents of a column in a database table. The classification may indicate and/or provide an estimation as to which documents or columns are most closely similar to each other, without making any assertion about the actual contents of the document or column. In some embodiments, a system may include counting some characteristic of the text. The characteristic may be chosen such that each text produces a set of counts. A statistical measure is then applied to determine the similarity of sets of counts associated with each pair of texts.

Abstract: A method performed on an electronic device for creating a proposal to a user. The proposal is created from an analysis of one or more personal electronically encoded items associated with one or more previously created perspectives unique to a user with each of the previously created perspectives representative of user interest and is based on similarities determined from the analysis. The proposal includes the creation of a new perspective, a new album, or a new perspective and a new album associated with the new perspective and the association therewith of one or more of the one or more analyzed personal electronically encoded items. Responsive to user acceptance of the proposal, the system creates the new perspective, the new album, or the new perspective and the new album associated with the new perspective and associates therewith one or more of the one or more analyzed personal electronically encoded items.

Abstract: Methods and apparatuses are provided for user interest modeling. A method may include receiving an input from a user for specifying one or more topics from among a predetermined hierarchy of topics and subtopics. The method may additionally include retrieving one or more documents associated with the user and extracting language tokens from the documents based, at least in part, on the specified topics. Corresponding apparatuses are also provided.

Abstract: Disclosed are a system for, and method of, determining whether records correspond to the same individual. The system and method provide such a determination with a known minimum level of confidence. That is, the system and method provide an indication that records correspond to the same individual along with an associated confidence level. The system and method may be used to link records in a database that correspond to the same individuals, creating entity representations in the database.

Abstract: The relevance of an object, such as a document resulting from a query, may be determined automatically. A graphical model-based technique is applied to determine the relevance of the object. The graphical model may represent relationships between actual and observed labels for the object, based on features of the object. The graphical model may take into account an assumption of noisy training data by modeling the noise.

Abstract: Online spelling correction/phrase completion is described herein. A computer-executable application receives a phrase prefix from a user, wherein the phrase prefix includes a first character sequence. A transformation probability is retrieved responsive to receipt of the phrase prefix, wherein the transformation probability indicates a probability that a second character sequence has been transformed into a first character sequence. A search is then executed over a trie to locate a most probable phrase completion based at least in part upon the transformation probability.

Abstract: The method for conducting a purchase involves obtaining a target item specification for purchasing a target item, wherein the target item specification comprises a target item description, a target purchase date, and a target price, obtaining, using a central processing unit (CPU), candidate item information related to a candidate item found on a merchant site consistent with the target item specification, wherein the candidate item information comprises a candidate item description and a candidate item price, populating a categorized entry in a user budget using the candidate item price and the target purchase date, wherein the candidate item price is no more than the target price, updating, using the CPU, the budget based on user transactions, generating a result by analyzing, using the CPU, the user budget with respect to the categorized entry, and submitting the result to a user for formulating a decision regarding whether to purchase the candidate item.

Abstract: A system that enables development and execution of predictive models comprises a centralized data management system, a data extraction tool a model validation tool and a model execution tool. In embodiments, a data management system includes a data management server that can be accessed via a web browser that stores data. An extraction tool includes a data filter adapted to filter data based on, for example, a population criteria, a sample size, and a date range criteria. A model validation tool validates the model. A model execution tool allows a user to score the model.

Abstract: A content recommendation system and method are provided in which content semantic topic analysis, user interest identification and per interest recommendations are used to deliver relevant and diversified content recommendations to the user. Semantic topic analysis is used to infer underlying topics in content items; for each content item, a topic distribution vector is derived with components that represent relevance of the content item to specific underlying topics. A user's long term and short term user interests are identified using the user's browsing history. Long term user interest(s) can be obtained by a weighted aggregation of topic distribution vectors of content items the user accessed. Short term interest can be represented by the topic distribution vector corresponding to a current content item. Using identified user's interests, relevant content items are selected for recommendations for the user.

Abstract: Methods, apparatus, and articles of manufacture to analyze and adjust demographic information of audience members are disclosed. An example method involves generating a first model based on reference demographic data corresponding to panelists and based on second demographic data and behavioral data from a database proprietor. The second demographic data and the behavioral data correspond to ones of the panelists having user accounts with the database proprietor. The method also involves using the first model to partition the second demographic data into a plurality of nodes, each node representing a respective subset of the second demographic data. The method also involves redistributing at least some of the second demographic data between at least some of the nodes to generate a second model.

Abstract: A tree structure has a node associated with each category of a hierarchy of item categories. Child nodes of the tree are associated with sub-categories of the categories associated with parent nodes. Training data including received queries and indicators of a selected item category for each received query is combined with the tree structure by associating each query with the node corresponding to the selected category of the query. When a query is received, a classifier is applied to the nodes to generate a probability that the query is intended to match an item of the category associated with the node. The classifier is applied until the probability is below a threshold. One or more categories associated with the nodes that are closest to the intent of the received query are selected and indicators of items of those categories that match the received query are output.

Abstract: Media item recommendation is described. In one example, a statistical model of media consumption is applied to media session consumption data from a community of users to infer parameters of the model. The model comprises a first probability distribution for each user defining a likelihood of the user having a latent characteristic for a session, and a second probability distribution for each latent characteristic defining a likelihood of a user selecting a media item given the latent characteristic. In another example, the inferred parameters are provided to a recommendation engine arranged to recommend media items. The recommendation engine uses the model with inferred parameters and data describing media items newly consumed by a user to infer a current latent characteristic for a current session of the user, and uses them to generate recommended media items for the user in the current session based on the current latent characteristic.

Abstract: A system and method is described herein that automatically determines if a user of a search engine is conducting a research mission and then provides one or more research tools, one or more specialized searches, one or more directed ads, and/or one or more marketplace events responsive to determining that the research mission is being conducted. The automatic provision of various events and/or tools responsive to determination of the research mission can advantageously improve the experience of the user conducting the research mission.

Abstract: Query-correction pairs can be extracted from search log data. Each query-correction pair can include an original query and a follow-up query, where the follow-up query meets one or more criteria for being identified as a correction of the original query, such as an indication of user input indicating the follow-up query is a correction for the original query. The query-correction pairs can be segmented to identify bi-phrases in the query-correction pairs. Probabilities of corrections between the bi-phrases can be estimated based on frequencies of matches in the query-correction pairs. Identifications of the bi-phrases and representations of the probabilities of those bi-phrases can be stored in a probabilistic model data structure.

Abstract: A method for providing search results in response to a search query is provided. The method includes receiving the search query from a user and generating a plurality of results in response to the search query. The plurality of results may be ranked according to an original relevancy score. The method further includes generating a click relevancy score for each of the plurality of results and re-ranking the plurality of results according to the click relevancy score.

Abstract: A model for impact analysis determines impact of part removal from a product. An entity is identifies that includes a plurality of sub-components. One or more performance measures associated with the entity are identified. One or more of the sub-components to be removed from the entity are identified. A substitution impact function is defined. Impact on said one or more performance measures is determined using the substitution impact function.

Abstract: Methods and systems for Web-scale entity relationship extraction are usable to build large-scale entity relationship graphs from any data corpora stored on a computer-readable medium or accessible through a network. Such entity relationship graphs may be used to navigate previously undiscoverable relationships among entities within data corpora. Additionally, the entity relationship extraction may be configured to utilize discriminative models to jointly model correlated data found within the selected corpora.

Abstract: In a computerized social network, expert and user chat sessions are stored and rated probabilistically. Later user requests for information are met with an expert ranking, based on a balance of similarities between expert profile and questions; similarity between expert profile and prior chat sessions, and dynamically updated chat session ratings. New sessions can be rated automatically with reference to keywords distilled from past sessions responsive to user ratings—and based on session length.

Abstract: A phonetic variation model building apparatus, having a phoneme database for recording at least a standard phonetic model of a language and a plurality of non-standardized phonemes of the language is provided. A phonetic variation identifier identifies a plurality of phonetic variations between the non-standardized phonemes and the standard phonetic model. A phonetic transformation calculator calculates a plurality of coefficients of a phonetic transformation function based on the phonetic variations and the phonetic transformation function. A phonetic variation model generator generates at least a phonetic variation model based on the standard phonetic model, the phonetic transformation function and the coefficients thereof.

Abstract: Hotspot analysis systems and methods are provided. The hotspot analysis system includes a database, a filtering module, a clustering module, and an analysis module. The database includes a plurality of records, each including context information having at least time information and position information. The filtering module filters the records according to current context information to obtain a plurality of filtered records. The clustering module clusters the filtered records into at least one hotspot cluster according to the position information of the filtered records, and generates a hotspot area for each hotspot cluster. The analysis module calculates integral hotness for each hotspot cluster according to the number of the filtered records in the hotspot cluster and the size of the hotspot area of the hotspot cluster, and generates at least hotspot area information according to the integral hotness and the hotspot area of each hotspot cluster.

Abstract: Sampling analysis includes classifying a plurality of query keywords into a plurality of query keyword subsets according to page view (PV) values associated with the plurality of query keywords, the plurality of query keywords being submitted by a plurality of users; determining a respective plurality of sample rates of a respective plurality of query keywords in a respective one of the plurality of query keyword subsets; and sampling query data in the respective one of the plurality of query keyword subsets according to the respective plurality of sample rates.

Abstract: The present invention provides a method, system and computer program product for developing a meta-model schema on the basis of one or more requirements associated with an enterprise process. The method includes defining various sets of meta-models based on the requirements and a predefined ontology. Each set of meta-models includes at least one meta-model that has been defined based on at least one other meta-model of the set of meta-models. Thereafter, the sets of meta-models defined for the corresponding requirements are integrated to develop the meta-model schema.

Abstract: There is disclosed a method, device, and software for presenting search results in a response to an end-user query. Search results are combined from results from a plurality of indexes, each of the search results having an associated key field. Index entries of each of the plurality of indexes are queried using an index-specific search algorithm to obtain a set of matching search results for each index, each matching search result having a quality of match specific to its index. A relative priority is determined for each of the plurality of indexes and the matching search results from the plurality of indexes are combined into a merged list of ordered search results based on the determined priority. A search result from a lower priority index is discarded in favor of any matching search result from a higher priority index.

Abstract: A term-by-document (or part-by-collection) matrix can be used to index documents (or collections) for information retrieval applications. Reducing the rank of the indexing matrix can further reduce the complexity of information retrieval. A method for index matrix rank reduction can involve computing a singular value decomposition and then retaining singular values based on the singular values corresponding to singular values of multiple topics. The expected singular values corresponding to a topic can be determined using the roots of a specially formed characteristic polynomial. The coefficients of the special characteristic polynomial can be based on computing the determinants of a Gram matrix of term (or part) probabilities, a method of recursion, or a method of recursion further weighted by the probability of document (or collection) lengths.

Abstract: A system and method for inferring and visualizing correlations of different business aspects for business transformation are provided. Business models, for instance, that may include business component model, business process model, value drivers and metrics model, application model, organization model, and solutions model are organized into a model topology data schema, and qualitative relationships and quantitative relationships may be configured among the entities or components of the business models. Correlations are inferred and visualized based on those relationships.

Abstract: Various technologies and techniques are disclosed for text based schema discovery and information extraction. Documents are analyzed to identify sections of the documents and a relationship between the sections. Statistics are stored regarding occurrences of items in the documents. A probabilistic model is generated based on the stored statistics. A database schema is generated with a plurality of tables based upon the probabilistic model. The documents are analyzed against the probabilistic model to determine how the documents map to the tables generated from the database schema. The tables are populated from the documents based on a result of the analysis against the probabilistic model.

Abstract: A method and structure for analyzing a database having non-text data in data fields and text in text fields. The invention first selects a subset of the database based upon criteria. The subset includes data field(s) and associated text field(s). The invention searches for data matching the criteria within structured data fields of the database. If the invention searches multiple databases, the invention creates shared dimensions for databases that do not share common attributes. The invention automatically selects a relatively short text phrase from the text fields that helps to explain the underlying meaning (i.e. unique text content) of a data subset selected using the non-text data fields.