Methods, systems and computer-readable media enable various techniques related to semantic navigation. One aspect is a technique for displaying semantically derived facets in the search engine interface. Each of the facets comprises faceted search results. Each of the faceted search results is displayed in association with user interface elements for including or excluding the faceted search result as additional search terms to subsequently refine the search query. Another aspect automatically infers new metadata from the content and from existing metadata and then automatically annotates the content with the new metadata to improve recall and navigation. Another aspect identifies semantic annotations by determining semantic connections between the semantic annotations and then dynamically generating a topic page based on the semantic connections.

One or more techniques and/or systems are provided for populating an information interface based upon social media data. For example, users may post, share, and/or discuss various information through social media sources. Accordingly, social media data may be obtained from such social media sources. The social media data may be grouped into sets of social media data based upon temporal information. Within the sets of social media data, social media entries may be clustered into topic clusters (e.g., a royal wedding topic cluster, a plane crash topic cluster, etc.). Event summaries may be generated for respective topic clusters. The event summaries may be used to populate timeslots of an information interface, such as a calendar or timeline, to create annotated timeslots. In this way, the information interface may provide users with an interactive view of events over a time period, such as a year-in-review, based upon social media data.

Embodiments of the invention include method, systems and computer program products for using a target similarity calculation to identify relevant content in a corpus of documents or records. The computer-implemented method includes creating, by a processor, a term frequency (TF) list for one or more documents of a corpus. The processor calculates an inverse document frequency (IDF) for each listed term. The processor calculates a TF-IDF for each listed term. The processor determines a similarity ranking for one or more documents of the corpus using a target similarity calculation using the TF-IDF for each listed term.

A data processing system identifies a first topic for a first table, identifies a second topic for a second table, collects at least one first table attribute comprising at least one row name for the first table, and collects at least one second table attribute comprising at least one row name for the second table. The at least one first table attribute and the at least one second table attribute are placed in at least one semantic category. The at least one first table attribute is converted into at least one semantic vector for the first table, and the at least one second table attribute is converted into at least one semantic vector for the second table. The at least one semantic vector for the first table is compared with the at least one semantic vector for the second table to identify as related at least one row of the first table and at least one row of the second table. The at least one row of the first table and the at least one row of the second table are provided to a communication device with an identification as related.

A method and a computer-readable medium for method for searching a plurality of documents. Each document is structured into a set of blocks and each block is associated with a block ID. The method includes receiving a search query including a search term having at least one search term attribute; identifying at least one block ID based on a correlation between the at least one search term attribute and the set of blocks; and identifying at least one document based on a correlation between the set of blocks and the documents. Methods for generating a data structure for searching documents are also described.

The present disclosure relates to devices and device configurations. In one embodiment, a process for providing application discovery and trial includes presenting a widget element on a display of the device, wherein the widget element includes graphical elements for a plurality of trial applications, and detecting a selection of one of the trial applications in the widget element. The process also includes updating the display to present a selected trial application based on the selection, wherein presentation of the selected trial application includes display of an overlay element, detecting a selection of the overlay element, and presenting a trial application control window based on the selection of the overlay element, the trial application control window including graphical elements for one or more of terminating, continuing and conversion of the selected trial application.

Systems and methods for indexing data include formulating an objective function to index a dataset, a portion of the dataset including supervision information. A data property component of the objective function is determined, which utilizes a property of the dataset to group data of the dataset. A supervised component of the objective function is determined, which utilizes the supervision information to group data of the dataset. The objective function is optimized using a processor based upon the data property component and the supervised component to partition a node into a plurality of child nodes.

The technology described herein provides for preliminary ranking of matching documents for a search query. A preliminary ranker uses score tables for scoring each matching document based on its relevant to a search query. The score table for a document stores pre-computed data used to derive a frequency of terms and other information in the document. The preliminary ranker uses the score table for each matching document and the terms form the search query to determine a score for each matching document. The lowest scoring documents are removed from further consideration by a final ranker.

Documents, such as those that may or will be the subject of a litigation, may be managed by automatically determining that a document, such as an email or other communication, is privileged or producible such that superfluous documents may be removed to improve data storage and reduce the burden on storage, processing, and communication resources. Additionally, documents such as emails may comprise attached or embedded documents (e.g., attachments) which may be similarly or independently classified from their associated email. After determining privilege, such as via metadata associated with a sender/receiver of an email, similarly categorized documents may be grouped for presentation and/or storage. The documents may be indexed, such as by entries within a production log, to further facilitate accurate production and management of non-privileged documents, as well as, the exclusion of privileged documents. Documents not required for production may be indexed and/or purged from storage.

Improved techniques for processing machine data are disclosed. Embodiments are operable to receive machine data input, interpret its meaning, and then represent that meaning in a knowledge base that grows over time with each new entry. The knowledge base enables extension of both syntax and lexicon, which are the main determinants of meaning. As new entries are added, the knowledge in the knowledge base grows. Over time, the knowledge base acquires more meaning. The disclosed machine data processing system includes entry type recognition, mapping entry types to semantic events, and building entries in the knowledge base based on the semantic event-entry type mapping. Data generated by this process may be used to conduct searches for patterns of semantic events across multiple different machine data sources. This information may then be used to perform useful work such as detecting security threats, identifying operational problems, or tracking customer purchases, etc.