Abstract: A method of constructing a plurality of downloadable files from an application file and a plurality of transcripts. The application file stores data blocks and implements an application. Each of the transcripts stores at least one order in which at least a portion of the data blocks of the application file were accessed by the application when executed previously. The transcripts are combined into a combined transcript storing at least one combined order comprising a combined portion of the data blocks. The data blocks of the combined portion are arranged in a data structure having an origin. A first set of data blocks within a predetermined distance from the origin is stored in at least one initial execution file. A second set of data blocks outside the predetermined distance from the origin is stored in downloadable sequence files.

Abstract: A method for dynamically clustering data items, the method comprising: receiving a plurality of data items originating from at least two sources, a plurality of distinct metadata details, and data indicative of associations between the data items and the metadata details, wherein each data item is associated with at least one metadata detail indicative of its owner, and wherein at least a first data item originating from a first source and a second data item originating from a second source are related data items associated with at least one shared metadata detail; grading probabilities of relationships between at least one of the data items and at least one of the metadata details; clustering the data items into one or more clusters, based on the calculated probabilities; and, optionally, sharing clusters and meta-clusters between users.

Abstract: Embodiments are directed towards managing data. An attributes engine may be employed to perform various actions, including: analyzing characteristics of model object features of a plurality of model objects; classifying the model object features based on the characteristics, such that the characteristics include a data type and values of the model object features; and associating similarity tasks with the model object features based on their classification. A similarity engine may then be employed to perform further actions, including: providing a similarity model that includes the similarity tasks; employing the similarity model to provide candidate similarity scores based on exemplar model objects labeled as being similar; modifying the similarity model based on the exemplar model objects and the candidate similarity scores; employing the modified similarity model to provide similarity scores for model objects based on the one or more similarity tasks.

Abstract: A method and apparatus for accessing a graph database having nodes and relationships describing an organization. An interface in a computer system receives a request from a client to access information about the organization. Further, the interface in the computer system retrieves the information from the graph database having nodes and relationships describing the organization. Still further, the interface in the computer system sends a portion of the information to the client based on how much of the information is displayable by the client.

Abstract: A method of dynamically computing an optimal materialization schedule for each column in a column oriented RDBMS. Dynamic column-specific materialization scheduling in a distributed column oriented RDBMS is optimized by choosing a materialization strategy based on execution cost including central processing unit (CPU), disk, and network costs for each individual exchange operator. The dynamic programming approach is computationally feasible because the optimal schedule for a sub-plan is path independent.

Abstract: Data mining systems and methods are disclosed for item recommendation based on frequent attribute-values associated with items. The system may determine commonalities in item attribute-values based on user transactions and identify frequent attribute-value tuples that include attribute-values that frequently co-occur in user transactions. The system may associate user interests with the frequent attribute-value tuples and recommend items to target users based thereon.

Abstract: Disclosed is a system for predicting an Elapsed Response Time (ERT) of a query to be executed in a production database. The system includes a database emulator module for creating an emulated database based on empty schema derived by extrapolating statistical information from the development environment. The system also includes an execution plan generation module for generating a query execution plan of the query. The system further includes a query classifying module for classifying each sub-query based on the operational parameters into at least one of a full table scan, a primary index scan, a fast index scan and a non-unique index scan. The system also includes a time determination module for executing each sub-query on the emulated database to determine an Input Output (IO) access time and an operator time.

Abstract: A system and method are disclosed for providing metric recommendations by a cloud event log analytics system. The log analytics system includes a user interface which allows users to view metric recommendations, view, modify, annotate, delete, or create log metrics. In a first embodiment, centroid vectors are created from metadata associated with user access of log metrics. The centroid vectors are compared to metrics vectors created from log metrics and the results are ranked and provided to users as metric recommendations. In a second embodiment, classification rules are inferred for metric matrix tables containing metadata about log metric usage. Classification rules are assigned to a decision tree used to calculate composite probabilities of interest of log metrics. A recommendation matrix incorporate the composite probabilities of interest to predict the degree of interest an analytics user may have in a log metric for a given role.

Abstract: An approach is provided for aggregating business data. Based on received columns, attributes, and keys of a dataset, the dataset is registered in a central hub of datasets which include data that is independently and locally maintained. Other datasets in the central hub that include columns, attributes, or keys that match the received columns, attributes, or keys, respectively, are determined and displayed. Responsive to receiving a user selection of one or more of the displayed datasets, cross-links between the dataset and each of the one or more selected datasets are generated. Based on a modification of a selected one of the cross-links and a second user interacting with the central hub, the modification and other cross-link(s) are displayed. Based on the second user's selection of the modification or one of the other cross-link(s), an analysis of data in the dataset is performed.

Abstract: A method is provided for enabling a software user to obtain answers based on information retrieved from Big Data systems to a query defined by a user. The method comprises: a) providing a software that comprises computational models, wherein each of the computational models is configured to provide answers to a different type of a user query, and at least one of the computational models is further configured to retrieve information from one or more Big Data systems; b) upon inputting the user query to the software, retrieving information from Big Data systems and presenting to the user a pre-determined series of queries and the results thereof, thereby reflecting to the user a multi-step process selected by the software for retrieving the answers to the query defined, based on information retrieved from the Big Data systems.

Abstract: In the examples provided herein, a controversy detection system includes a classifier engine to classify each of a plurality of comments about a publication as controversial or non-controversial. The system also includes a controversy detector engine to determine, based on the classification of the plurality of comments, whether the publication is controversial or non-controversial.

Abstract: Disclosed herein are system, method, and computer program product embodiments for providing point in time recovery on a database. An embodiment operates by determining that one or more values were written to one of a plurality of database nodes of a database as part of a write transaction. The one or more data pages to which the one or more values were written are copied to a storage location of a backup corresponding to the write transaction. The storage location of the one or more data pages in the backup are written to a location in a transaction log corresponding to the write transaction.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of clauses in a first set of content items comprising unstructured data. Next, the system obtains a set of stop words comprising high-frequency words that occur in a second set of content items. The system then automatically extracts a set of topics from the set of clauses by generating a set of n-grams from the set of clauses and excluding a first n-gram in the set of n-grams from the set of topics when the first n-gram contains a word in the set of stop words in a pre-specified position of the first n-gram. Finally, the system displays the set of topics to a user to improve understanding of the first set of content items by the user without requiring the user to manually analyze the first set of content items.

Abstract: Methods and apparatuses for identifying a track for a target are disclosed herein. In a general embodiment, trees for targets are identified. Each tree in the trees includes observations that are connected to each other by branches and each observation has a score. A selected track in a tree is identified within the trees with an observation having a highest score. A group of branches is added to the selected track from other trees other than the tree having the selected track to form the track for a target, enabling reducing processing resources used to identify the track.

Abstract: A first search term input by a user is obtained. The first search term is matched with at least one keyword in a list such as an offline lists to select at least one keyword from the list. Each keyword in the list corresponds to at least one search recommendation respectively. A search recommendation corresponding to the at least one keyword selected from the offline list is obtained and provided to the user as a search recommendation of the first search term. For example, a historical user behavior relating to the keyword is obtained from a log record. A document generated by the historical user behavior is obtained. At least one candidate recommendations are obtained from text segmentation of the document. The present techniques provide a large range of selection of search recommendations, reduce a number of user searches, and further reduce search time and traffic.

Abstract: System, computer implemented method and computer program product for preparing and navigating a query tree including a plurality of query nodes and informational nodes. Each query node is associated with a prompt, branching criteria and keywords. A current query node provides a prompt to a user and a user response is received and analyzed to identify branching criteria and keywords from the user response. The method navigates to another node in the query tree in consideration of the branching criteria received in the user response and a comparison between the keywords received in the user response and the keywords associated with the query nodes. The comparison may validate navigation to a destination node corresponding to the branching criteria or the comparison may indicate incorrect navigation of the query tree. Corrective navigation can be implemented in various ways based upon the keywords received in the user response.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of content items and a set of topics in the set of content items. For each topic in the set of topics, the system automatically extracts a set of attributes that provides a context for the topic from a subset of the content items containing the topic. The system then displays the set of attributes in the context of the topic to improve understanding of the set of content items by the user without requiring the user to manually analyze the set of content items.

Abstract: In accordance with embodiments disclosed herein, there are provided methods, systems, and apparatuses for implementing a session table framework including, for example, receiving a request at a host organization from a client device, in which such a request specifies an application available via the host organization; generating a user session unique to the client device in a memory of the host organization; creating a user session data table within the user session; processing the request via the application specified by the request on behalf of the client device; updating the user session data table based on the processing of the request; and transmitting a response to the client device responsive to the request.

Abstract: A testing and extract, transform and load (TETL) system is operable to interface with test platforms testing hardware or software components of information technology systems. The TETL system can execute extract, transform and load operations to load test data into a data warehouse and facilitates evaluating the test data across projects, entities and domains.

Abstract: Systems and methods are provided for generating organization data for an efficient presentation and/or organization of a collection of items. In some embodiments, the organization data may be based on metadata associated with items, such as keywords. The metadata may be generated from natural language processing of the items. Organization data and/or a hierarchical data organization may be a tree data structure that can be efficiently navigated to reach and/or locate an item. In some embodiments, organization data may be automatically updated in response to a document removal, addition, and/or a user selection. For example, as items are removed and/or added to the collection, keywords, counts, directories, nodes, and/or levels of the organization data may update and/or change to reflect the updated collection of items.