Abstract: In one embodiment, a method includes receiving, from a client system associated with a user, a search query comprising a number of query terms, generating a query match-matrix for the search query, identifying a number of objects matching the search query, retrieving, for each identified object, an object match-matrix for the identified object, constructing, for each identified object, a three-dimensional tensor for the identified object, computing, for each identified object, a relevance score based on the tensor for the identified object, ranking the identified objects based on their respective relevance scores, and sending, to the first client system in response to the search query, instructions for generating a search-results interface for presentation to the user.

Abstract: In one embodiment, a method includes retrieving multiple posts containing each of the query terms after receiving a search query for posts from a user of an online social network, identifying, from an index of known phrases, one or more known phrases in the text of the retrieved posts, filtering the retrieved posts to generate a filtered set of posts, wherein the filtering comprises removing each post not containing at least one of the identified known phrases, computing features for each of the identified known phrases, calculating a score for each post in the filtered set based on the features of the identified known phrases, ranking the posts based on the calculated scores, and sending instructions, to the client system, for generating a search-results interface comprising references to one or more of the posts presented in ranked order.

Abstract: In one embodiment, a method includes receiving a search query from a client system of a first user; parsing the search query into n-grams, and calculating confidence-scores for entities in a set of query-analysis-entities based on the n-grams, each confidence-score representing a probability that one or more of the n-grams are intended to reference a respective entity; determining a set of search results matching the search query, and calculating entity-frequencies corresponding to entities in a set of results-analysis-entities based on a histogram analysis of the set of search results; calculating a filter-score entities in a set of prospective-entities, which includes entities from the set of query-analysis-entities and the set of results-analysis-entities, based on the respective confidence-score and entity-frequency; and sending, to the client system, suggested filters corresponding to entities having a filter-score greater than a threshold filter-score, the suggested filters being selectable to modify th

Abstract: In one embodiment, a method includes receiving, from a client system associated with a user, a search query comprising a number of query terms, generating a query match-matrix for the search query, identifying a number of objects matching the search query, retrieving, for each identified object, an object match-matrix for the identified object, constructing, for each identified object, a three-dimensional tensor for the identified object, computing, for each identified object, a relevance score based on the tensor for the identified object, ranking the identified objects based on their respective relevance scores, and sending, to the first client system in response to the search query, instructions for generating a search-results interface for presentation to the user.

Abstract: In one embodiment, a method includes retrieving multiple posts containing each of the query terms after receiving a search query for posts from a user of an online social network, identifying, from an index of known phrases, one or more known phrases in the text of the retrieved posts, filtering the retrieved posts to generate a filtered set of posts, wherein the filtering comprises removing each post not containing at least one of the identified known phrases, computing features for each of the identified known phrases, calculating a score for each post in the filtered set based on the features of the identified known phrases, ranking the posts based on the calculated scores, and sending instructions, to the client system, for generating a search-results interface comprising references to one or more of the posts presented in ranked order.

Abstract: In one embodiment, a method includes receiving a search query from a client system of a first user; parsing the search query into n-grams, and calculating confidence-scores for entities in a set of query-analysis-entities based on the n-grams, each confidence-score representing a probability that one or more of the n-grams are intended to reference a respective entity; determining a set of search results matching the search query, and calculating entity-frequencies corresponding to entities in a set of results-analysis-entities based on a histogram analysis of the set of search results; calculating a filter-score entities in a set of prospective-entities, which includes entities from the set of query-analysis-entities and the set of results-analysis-entities, based on the respective confidence-score and entity-frequency; and sending, to the client system, suggested filters corresponding to entities having a filter-score greater than a threshold filter-score, the suggested filters being selectable to modify th

Abstract: The present invention is a sentence realization system that processes an abstract linguistic representation (ALR) of a sentence into a structure that can be fully realizable. The system includes a tree conversion component that receives the ALR and generates a basic syntax tree from the ALR. A global movement component then receives the basic syntax tree and hierarchically orders child nodes in that syntax tree relative to ancestor nodes. An intra-constituent ordering component then establishes a linear order among the nodes such that the syntax tree is fully ordered. A surface cleanup component receives the fully ordered tree and performs a number of realization operations to generate surface realizations for constituents that are still represented in an abstract way in the fully ordered syntax tree.

Abstract: The present invention is a tree ordering component within a sentence realization system which receives an unordered syntax tree and generates a ranked list of alternative ordered syntax trees from the unordered syntax tree. The present invention also includes statistical models of constituent structure employed by the tree ordering component in scoring the alternative ordered trees.

Abstract: The present invention provides a system for identifying, extracting, clustering and analyzing sentiment-bearing text. In one embodiment, the invention implements a pipeline capable of accessing raw text and presenting it in a highly usable and intuitive way.

Abstract: The present invention provides a system for identifying, extracting, clustering and analyzing sentiment-bearing text. In one embodiment, the invention implements a pipeline capable of accessing raw text and presenting it in a highly usable and intuitive way.

Abstract: A location history is a collection of locations over time for an object. A stay is a single instance of an object spending some time in one place, and a destination is any place where one or more objects have experienced a stay. Location histories are parsed using stays and destinations. In a described implementation, each location of a location history is recorded as a spatial position and a corresponding time at which the spatial position is acquired. Stays are extracted from a location history by analyzing locations thereof with regard to a temporal threshold and a spatial threshold. Specifically, two or more locations are considered a stay if they exceed a minimum stay duration and are within a maximum roaming distance. Each stay includes a location, a starting time, and an ending time. Destinations are produced from the extracted stays using a clustering operation and a predetermined scaling factor.

Abstract: A method or module for creating an Language Neutral Syntax (LNS) representation of a sentence from a language particular syntax representation such as found in the Penn Treebank for use by different applications. The method or module includes a node generator configured to create hierarchical and dependent nodes using phrasal and constituent nodes of the language particular syntax. A node dependency generator is configured to create an unordered hierarchical dependency structure for the hierarchical and dependent nodes using a semantic relation between the hierarchical and dependent nodes derived from the language particular syntax.

Abstract: A method of decoding an input semantic structure to generate an output semantic structure. A set of transfer mappings are provided. A score is calculated for at least one transfer mapping in the set of transfer mappings using a statistical model. At least one transfer mapping is selected based on the score and used to construct the output semantic structure.

Abstract: The present invention relates to systems and methods that determine intent for received data (e.g., email, voice, graphics . . . ) and respond to the data based on the intent. The systems and methods employ various combinations of features based on shallow and deep linguistic analysis (e.g., semantic and syntactic) to yield very high accuracy. The systems and methods analyze and categorize received data to locate data that can include intent. This data can be further refined by extracting features related to the intent. The features can be utilized by a classifier to determine the intent. If the intent warrants a response, the data are further scrutinized and reformulated to generate a description that is indicative of the intent. The reformulation can include representing the features in a logical form, transforming the form and generating a description of the intent that can be presented to a user visually and/or audibly.

Abstract: The present invention is a tree ordering component within a sentence realization system which receives an unordered syntax tree and generates a ranked list of alternative ordered syntax trees from the unordered syntax tree. The present invention also includes statistical models of constituent structure employed by the tree ordering component in scoring the alternative ordered trees.

Abstract: The present invention is a sentence realization system that processes an abstract linguistic representation (ALR) of a sentence into a structure that can be fully realizable. The system includes a tree conversion component that receives the ALR and generates a basic syntax tree from the ALR. A global movement component then receives the basic syntax tree and hierarchically orders child nodes in that syntax tree relative to ancestor nodes. An intra-constituent ordering component then establishes a linear order among the nodes such that the syntax tree is fully ordered. A surface cleanup component receives the fully ordered tree and performs a number of realization operations to generate surface realizations for constituents that are still represented in an abstract way in the fully ordered syntax tree.