Included are a 2D processing unit 11 that generates 2D latitude and longitude information by dimensionally compressing a feature vector generated from target information, and a map generation unit 12 that generates a 2D map in which a plurality of pieces of target information is plotted on a 2D plane based on a plurality of pieces of latitude and longitude information generated for a plurality of pieces of target information. A plurality of pieces of target information is plotted based on a feature vector in a coordinate system of a closed space having finite latitude and longitude values, so that a plot position of target information can be appropriately determined in a wide coordinate space based on latitude and longitude without performing processing such as defining a finite target area in a coordinate system of an infinite open space, and a state in which pieces of target information having a high similarity are plotted in a shape of a mass at close positions is likely to occur appropriately at a plurality of locations.

Provided herein are systems, methods and computer readable media for classification and tagging of textual data. An example method may include accessing a corpus comprising a plurality of documents, each document having one or more labels indicative of services offered by a merchant, generating a query based on extracted features and the documents, generating a precision score for at least a portion of the generated query and selecting a subset of the generated queries based on an assigned precision score satisfying a precision score threshold, the selected subset of the generated queries configured to provide an indication of one or more labels to be applied to machine readable text. A second example method, utilized for tagging machine readable text with unknown labels, may include assigning a label to textual portions of the machine readable text based on results of the application of the queries.

A process including obtaining a set of natural-language text documents that discuss a topic, the set of documents containing different states of knowledge about the topic at different times. The process includes selecting an ontology from among a plurality of ontologies that correspond to different domains of knowledge, the selection being based on the ontology corresponding to a domain of knowledge including the topic. The process includes identifying concepts discussed in the documents using the ontology and detecting changes in at least some of the concepts over time based on differences between discussion of the concepts in documents authored at different times. The process includes updating natural language instructions on the topic based on the detected changes in the concepts and storing the updated natural language instructions in memory.

Techniques are described herein for optimizing the presentation of content through obtaining viewership metrics, generating multiple renditions of presentations of content, and selecting optimized renditions of content. One aspect includes associating a request for viewership metrics with a presentation of content, publishing the presentation of content, and receiving information of the viewership metrics associated with the presentation. Another aspect includes copying a presentation of a content item, creating a second presentation of the content item for publishing over one or more channels, and linking the presentation of the content item to the second presentation of the content item, such that a change to one propagates to the other of the presentation of the content item or the second presentation of the content item. In yet another aspect, a content rendition may be selected for presentation based on performance of the rendition out of multiple renditions in an auction.

A mechanism is provided in a data processing system to implement an annotator for annotating content using context-based surface forms. The mechanism receives a dictionary data structure of surface forms comprising a plurality of regular expressions and input content. The mechanism compares a given span of text in the input content to each regular expression in the dictionary data structure. Responsive to the given span of text matching a given regular expression, an annotator annotates the span of text with a content indicator corresponding to a content category associated with the dictionary data structure. The mechanism performs a natural language processing operation on the input content based on results of the annotation.

Within an environment in which users converse at least partly with human agents to accomplish a desired task, a server assists the agents by identifying workflows that are most applicable to the current conversation. Workflow selection functionality identifies one or more candidate workflows based on techniques such as user intent inference, conversation state tracking, or search, according to various embodiments. The identified candidate workflows are either automatically selected on behalf of the agent, or are presented to the agent for manual selection.

Among pieces of attribute information contained in a document, user-designated attribute information and other attribute information that may give additional value to the user-designated attribute information are accurately and efficiently presented. An attribute extraction apparatus includes a storage section that stores a document; and a computing section that executes a process for calculating a predetermined index on the basis of the document's structure with respect to a relationship between a plurality of pieces of attribute information described in the document, and a process for calculating an importance degree of each piece of the attribute information other than predetermined attribute information for the predetermined attribute information on the basis of at least one of the index and a predetermined statistical property with respect to a relationship between the predetermined attribute information and the attribute information other than the predetermined attribute information among the plurality of pieces of the attribute information.

Embodiments of the present disclosure relate to a method and apparatus for managing a document index. The method comprises determining an independently updatable field in a plurality of documents, the independently updatable field comprising at least one item. The method further comprises creating an index for an item in the independently updatable field, the index containing an identifier of a document comprising the item, the document being included in the plurality of documents. Furthermore, the method further comprises storing the identifier of the document in blocks such that the index is updatable without modifying the identifier of the document.

Methods and systems are disclosed for generating and using a knowledge graph. In an aspect, the knowledge graph may be generated based on data fields for one or more datasets associated with one or more parameters extracted from a group of chart data structures. In another aspect, a query dataset may be analyzed, and one or more query data fields may be extracted from the query dataset. The one or more query data fields may be compared to a knowledge graph stored in a graph database to determine one or more result data fields. A context may be determined for each of the one or more result data fields, and an associated data set may be determined. Based on the context, each of the associated data sets may be scored, and a recommended analysis may be presented to a user.

According to one embodiment, content keyword elements (CKEs) are determined based on content keywords (CKs) associated with content items. Query keyword elements (QKEs) are determined based on query keywords (QKs) associated with search queries. A first search query having one or more query keywords represented by a first QKE. A first content keyword represented by a first CKE that matches the first QKE is identified. A new entry in a query-to-CK (query/CK) whitelist table to map the first search query to the first content keyword. The query/CK whitelist table includes a number of entries, each entry mapping a search query to one or more content keywords. The query/CK whitelist table is utilized to identify content items in response to a subsequent search query.