Abstract: A domain-specific sentiment classifier that can be used to score the polarity and magnitude of sentiment expressed by domain-specific documents is created. A domain-independent sentiment lexicon is established and a classifier uses the lexicon to score sentiment of domain-specific documents. Sets of high-sentiment documents having positive and negative polarities are identified. The n-grams within the high-sentiment documents are filtered to remove extremely common n-grams. The filtered n-grams are saved as a domain-specific sentiment lexicon and are used as features in a model. The model is trained using a set of training documents which may be manually or automatically labeled as to their overall sentiment to produce sentiment scores for the n-grams in the domain-specific sentiment lexicon. This lexicon is used by the domain-specific sentiment classifier.

Abstract: Disclosed herein is a method, a system and a computer product for generating a snippet for an entity, wherein each snippet comprises a plurality of sentiments about the entity. One or more textual reviews associated with the entity is selected. A plurality of sentiment phrases are identified based on the one or more textual reviews, wherein each sentiment phrase comprises a sentiment about the entity. One or more sentiment phrases from the plurality of sentiment phrases are selected to generate a snippet.

Abstract: A domain-specific sentiment classifier that can be used to score the polarity and magnitude of sentiment expressed by domain-specific documents is created. A domain-independent sentiment lexicon is established and a classifier uses the lexicon to score sentiment of domain-specific documents. Sets of high-sentiment documents having positive and negative polarities are identified. The n-grams within the high-sentiment documents are filtered to remove extremely common n-grams. The filtered n-grams are saved as a domain-specific sentiment lexicon and are used as features in a model. The model is trained using a set of training documents which may be manually or automatically labeled as to their overall sentiment to produce sentiment scores for the n-grams in the domain-specific sentiment lexicon. This lexicon is used by the domain-specific sentiment classifier.

Abstract: Disclosed herein is a method, a system and a computer product for generating a snippet for an entity, wherein each snippet comprises a plurality of sentiments about the entity. One or more textual reviews associated with the entity is selected. A plurality of sentiment phrases are identified based on the one or more textual reviews, wherein each sentiment phrase comprises a sentiment about the entity. One or more sentiment phrases from the plurality of sentiment phrases are selected to generate a snippet.

Abstract: A domain-specific sentiment classifier that can be used to score the polarity and magnitude of sentiment expressed by domain-specific documents is created. A domain-independent sentiment lexicon is established and a classifier uses the lexicon to score sentiment of domain-specific documents. Sets of high-sentiment documents having positive and negative polarities are identified. The n-grams within the high-sentiment documents are filtered to remove extremely common n-grams. The filtered n-grams are saved as a domain-specific sentiment lexicon and are used as features in a model. The model is trained using a set of training documents which may be manually or automatically labeled as to their overall sentiment to produce sentiment scores for the n-grams in the domain-specific sentiment lexicon. This lexicon is used by the domain-specific sentiment classifier.

Abstract: A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.

Abstract: A fact repository stores objects. Each object includes a collection of facts, where a fact comprises an attribute and a value. A set of objects from the fact repository are designated for analysis. The presentation engine presents the facts of the objects in a user interface (UI) having a table. Through manipulation of the UI, an end-user can add or remove facts from the table, and sort the table based on the values of particular facts. The presentation engine also presents the facts of the objects in a UI having a graph. Through manipulation of the UI, the end-user can add or remove facts from the graph, and can sort the facts shown in the graph based on values that are shown, or not shown, in the graph. The presentation engine can further present the facts of the objects in UIs including maps and timelines.

Abstract: A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.

Abstract: A corpus contains information including text from books and metadata about the books. The book texts mention entities of various types, such as location, date, event, and person entities. An entity importance engine analyzes the information in the corpus to identify the entities mentioned therein, and ranks the entities using query-independent importance scores. The importance scores can be based in part on the contexts in which the entities are mentioned by the books. A presentation engine enables searching of the corpus to identify books satisfying a search query. The presentation engine presents information about a designated book. Entities mentioned in the book are presented in a style selected to enhance comprehension and utility. For example, location entities can be presented on a map with markers showing the locations of the entities. The number of entities presented are limited and ordered based on the query-independent importance scores.

Abstract: A set of objects having facts is established. Facts of objects having positions in an order are identified. Some facts explicitly describe the positions in the linear order, while are facts do not explicitly describe the positions. The facts are presented in the order on a linear graph, such as a timeline. Facts of the objects describing geographic positions are presented on a map.

Abstract: Methods, systems, and apparatus, including computer programs stored on computer storage media, for populating a structured presentation with new values. One aspect can be embodied in machine-implemented methods that include the actions of receiving description data describing a preexisting structured presentation, comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new value that is relevant to the preexisting structured presentation, adding the new value to the preexisting structured presentation to form a new structured presentation, and outputting instructions for visually presenting the new structured presentation.

Abstract: Methods, systems, and apparatus, including computer programs stored on computer storage media, for retrieval and display of information from an electronic document collection. One aspect can be embodied in machine-implemented methods that include the actions of receiving description data describing a preexisting structured presentation, comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new attribute that is relevant to the preexisting structured presentation, adding an identifier of the new attribute to the preexisting structured presentation to form an expanded structured presentation, and outputting instructions for presenting the expanded structured presentation.

Abstract: Methods, systems, and apparatus, including computer programs stored on computer storage media, for retrieval and display of information from an unstructured electronic document collection. One aspect can be embodied in machine-implemented methods that include the actions of receiving a machine-readable search query from a user and responding to the search query with instructions for presenting the user with a structured presentation of instances relevant to the search query. A visual presentation of the structured presentation denotes associations between the instances and values that characterize attributes of the instances by virtue of an arrangement of identifiers of the instances and the values.

Abstract: Methods, systems, and apparatus, including computer programs stored on computer storage media, for retrieval and display of information from an electronic document collection. In one aspect, a machine-implemented method includes the actions of receiving description data describing a preexisting structured presentation, comparing characteristics of the preexisting structured presentation with content of electronic documents in an unstructured collection of electronic documents to locate electronic documents that identify a new instance that is relevant to the preexisting structured presentation, adding an identifier of the new instance to the preexisting structured presentation to form an expanded structured presentation, and outputting instructions for presenting the expanded structured presentation.

Abstract: Metadata is used to determine rules that can be applied to facts. In one embodiment, correlations are identified among types of objects and the attributes of the facts associated with those objects. In another embodiment, correlations are identified among types of objects, the attributes of the facts associated with the objects, and the format and/or range of the values of the facts having those attributes. When a correlation exists between objects of a given type and the attributes of the facts associated with objects of that type, a rule is created for objects of that type. The rule is applied to objects of the given type.

Abstract: Described is a mechanism for issuing an event notification message, from a first program to a second program, to indicate that an action occurred within the first program, where the event notification message includes a parameter that indicates that the action is one of a group of possible actions. More specifically, in an application configured to edit documents created with the eXtensible Markup Language XML, the occurrence of an XML-related action causes the event notification message to be issued. The XML-related action may be either an XML-related move action, an XML-related insert action, or an XML-related delete action. In this way, a single event notification message can be used to indicate the occurrence of three different types of actions while editing an XML document.

Abstract: Disclosed herein is a method, a system and a computer product for generating a snippet for an entity, wherein each snippet comprises a plurality of sentiments about the entity. One or more textual reviews associated with the entity is selected. A plurality of sentiment phrases are identified based on the one or more textual reviews, wherein each sentiment phrase comprises a sentiment about the entity. One or more sentiment phrases from the plurality of sentiment phrases are selected to generate a snippet.

Abstract: A fact repository stores objects. Each object includes a collection of facts, where a fact comprises an attribute and a value. A set of objects from the fact repository are designated for analysis. The presentation engine presents the facts of the objects in a user interface (UI) having a table. Through manipulation of the UI, an end-user can add or remove facts from the table, and sort the table based on the values of particular facts. The presentation engine also presents the facts of the objects in a UI having a graph. Through manipulation of the UI, the end-user can add or remove facts from the graph, and can sort the facts shown in the graph based on values that are shown, or not shown, in the graph. The presentation engine can further present the facts of the objects in UIs including maps and timelines.

Abstract: A computer-implemented method for providing a candidate list of alternatives for a text selection containing text from multiple input sources, each of which can be stochastic (such as a speech recognition unit, handwriting recognition unit, or input method editor) or non-stochastic (such as a keyboard and mouse). A text component of the text selection may be the result of data processed through a series of stochastic input sources, such as speech input that is converted to text by a speech recognition unit before being used as input into an input method editor. To determine alternatives for the text selection, a stochastic input combiner parses the text selection into text components from different input sources. For each stochastic text component, the combiner retrieves a stochastic model containing alternatives for the text component.

Abstract: An adaptive compression technique which is an improvement to Lempel-Ziv (LZ) compression techniques, both as applied for purposes of reducing required storage space and for reducing the transmission time associated with transferring data from point to point. Pre-filled compression dictionaries are utilized to address the problem with prior Lempel-Ziv techniques in which the compression software starts with an empty compression dictionary, whereby little compression is achieved until the dictionary has been filled with sequences common in the data being compressed. In accordance with the invention, the compression dictionary is pre-filled, prior to the beginning of the data compression, with letter sequences, words and/or phrases frequent in the domain from which the data being compressed is drawn. The letter sequences, words, and/or phrases used in the pre-filled compression dictionary may be determined by statistically sampling text data from the same genre of text.