Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.

Logic may adjust communications between customers. Logic may cluster customers into a first group associated with a first subset of synonyms and a second group associated with a second subset of the synonyms. Logic may associate a first tag with the first group and with each of the synonyms of the first subset. Logic may associate a second tag with the second group and with each of the synonyms of the second subset. Logic may associate one or more models with pairs of the groups. A first pair may comprise the first group and the second group. The first model associated with the first pair may adjust words in communications between the first group and the second group, based on the synonyms associated with the first pair, by replacement of words in a communication between customers of the first subset and customers of the second sub set.

System and method for the indexing and searching of multilingual documents are disclosed.

Technologies are described herein for document collaboration discovery. A collaboration system enables users to collaboratively author documents. The collaboration system receives edits to a document in real or near real time, and indexes the edits in a search index. The collaboration system can also receive and index metadata associated with the document. The collaboration system can also receive a search query from a user and perform a search of the search index. If the document is identified by the search, the user can request to be admitted as an active editor of the document. The user can also request to join a real-time messaging session with other active editors of the document. The active editors can be notified of the search terms that led the user to the document, and indicate whether the user is to be admitted to the document as an active editor or the real-time messaging session.

The technology described herein provides for identifying matching documents for a search query using a bit vector search index. When a search query is received, a term is identified from the search index, and a number of bit vectors corresponding to the term are identified. Each bit vector comprises an array of bits in which at least one bit in each bit vector indicates that a corresponding document includes the term. Each bit vector also includes other bits indicating other documents include other terms. The identified bit vectors are intersected to identify matching documents that contain the term.

Systems and methods for determining that artificial commands, in excess of a threshold value, are detected by multiple voice activated electronic devices is described herein. In some embodiments, numerous voice activated electronic devices may send audio data representing a phrase to a backend system at a substantially same time. Text data representing the phrase, and counts for instances of that text data, may be generated. If the number of counts exceeds a predefined threshold, the backend system may cause any remaining response generation functionality that particular command that is in excess of the predefined threshold to be stopped, and those devices returned to a sleep state. In some embodiments, a sound profile unique to the phrase that caused the excess of the predefined threshold may be generated such that future instances of the same phrase may be recognized prior to text data being generated, conserving the backend system's resources.

A method can include: reordering an enriched inverted index associated with a database, the enriched inverted index including a first inverted list having a first plurality of current document identifiers of records that contain a first data value, the enriched inverted index further including a first data structure storing enrichment data, the reordering of the enriched inverted index comprising: generating an ordinal sequence corresponding to an order of a first plurality of current document identifiers that include a change of at least one of the first plurality of current document identifiers to a new document identifier; determining a reordered ordinal sequence corresponding to a sorted order of the second plurality of document identifiers; separately reordering, based at least on the reordered ordinal sequence, the first plurality of current document identifiers in the first inverted list and the enrichment data in the first data structure.

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.

A semantic indexing system, the semantic indexing system comprising a processing resource configured to: provide a corpus comprising a plurality of textual documents, wherein (a) each of the textual documents being composed of one or more sentences; (b) each of the sentences being composed of one or more statements; and generate an index, the index mapping each of the statements to one or more frames; wherein each frame defines a structure that carries a semantic meaning, thereby enabling searching the corpus by the semantic meaning of a search statement.

A computer-implemented method for electronically identifying new content in a digital document. The method includes receiving a digital document, utilizing a NLP pipeline to identify one or more articles of subject matter content, together with their respective relationships, contained within the digital document. The method further includes generating, by the NLP pipeline, a knowledge graph, based on the one or more relationships between the one or more articles of subject matter content contained within the digital document, and comparing the generated knowledge graph to one or more stored knowledge graphs based on a novelty-criteria, to determine whether the identified one or more articles of subject matter content, together with their respective relationships, are represented in the one or more stored knowledge graphs. The method further includes communicating one or more portions of the digital document that were determined to not be contained within the one or more stored knowledge graphs.