Abstract: Disclosed is a character inputting method, device and an intelligent terminal, the method including: when a virtual key in a virtual on-screen keyboard layout is selected, invoking a first probability statistical table matching at least one character having been displayed by at least one virtual key having been selected; displaying a part of the candidate characters with the highest combination probabilities or all of the candidate characters in the invoked first probability statistical table respectively on virtual keys in the virtual on-screen keyboard layout, and resetting focus on a preset virtual key, wherein any candidate character displayed on a virtual key configured with higher level has higher combination probability; and performing operations above periodically until an ideogram or a character sequence to be input is selected, and inputting the selected ideogram or the character sequence selected in an input area.

Abstract: Disclosed is a character inputting method, device and an intelligent terminal, the method including: when a virtual key in a virtual on-screen keyboard layout is selected, invoking a first probability statistical table matching at least one character having been displayed by at least one virtual key having been selected; displaying a part of the candidate characters with the highest combination probabilities or all of the candidate characters in the invoked first probability statistical table respectively on virtual keys in the virtual on-screen keyboard layout, and resetting focus on a preset virtual key, wherein any candidate character displayed on a virtual key configured with higher level has higher combination probability; and performing operations above periodically until an ideogram or a character sequence to be input is selected, and inputting the selected ideogram or the character sequence selected in an input area.

Abstract: Disclosed is a character inputting method, device and an intelligent terminal, the method including: when a virtual key in a virtual on-screen keyboard layout is selected, invoking a first probability statistical table matching at least one character having been displayed by at least one virtual key having been selected; displaying a part of the candidate characters with the highest combination probabilities or all of the candidate characters in the invoked first probability statistical table respectively on virtual keys in the virtual on-screen keyboard layout, and resetting focus on a preset virtual key, wherein any candidate character displayed on a virtual key configured with higher level has higher combination probability; and performing operations above periodically until an ideogram or a character sequence to be input is selected, and inputting the selected ideogram or the character sequence selected in an input area.

Abstract: A query is defined that has an answer formed of terms from electronic documents. A repository having facts is examined to identify attributes corresponding to terms in the query. The electronic documents are examined to find other terms that commonly appear near the query terms. Hypothetical facts representing possible answers to the query are created based on the information identified in the fact repository and the commonly-appearing terms. These hypothetical facts are corroborated using the electronic documents to determine how many documents support each fact. Additionally, contextual clues in the documents are examined to determine whether the hypothetical facts can be expanded to include additional terms. A hypothetical fact that is supported by at least a certain number of documents, and is not contained within another fact with at least the same level of support, is presented as likely correct.

Abstract: A system and method for extracting facts from documents. A fact is extracted from a first document. The attribute and value of the fact extracted from the first document are used as a seed attribute-value pair. A second document containing the seed attribute-value pair is analyzed to determine a contextual pattern used in the second document. The contextual pattern is used to extract other attribute-value pairs from the second document. The extracted attributes and values are stored as facts.

Abstract: The application disclose a projection display system and method, and the projection display system includes a light source module, a DMD, and an imaging module, wherein the light source module is configured to illuminate the DMD with light rays emitted periodically at different angles; and the DMD is configured to receive the light rays emitted by the light source module according to a corresponding relationship between an angle and a part of image, and to reflect the received light rays emitted by the light source module in response to a driver signal corresponding to any part of image to be displayed, to thereby generate and transmit reflected light rays corresponding to respective pixels of the part of image to the imaging module.

Abstract: Disclosed is a character inputting method, device and an intelligent terminal, the method including: when a virtual key in a virtual on-screen keyboard layout is selected, invoking a first probability statistical table matching at least one character having been displayed by at least one virtual key having been selected; displaying a part of the candidate characters with the highest combination probabilities or all of the candidate characters in the invoked first probability statistical table respectively on virtual keys in the virtual on-screen keyboard layout, and resetting focus on a preset virtual key, wherein any candidate character displayed on a virtual key configured with higher level has higher combination probability; and performing operations above periodically until an ideogram or a character sequence to be input is selected, and inputting the selected ideogram or the character sequence selected in an input area.

Abstract: A system and method for corroborating a set of facts. If the anchor text of the references to a document matches the name of a set of facts, the referenced document is used to corroborate the set of facts. By analyzing the anchor text of the references to the document, the system is capable of determining if a document is relevant to the set of facts. These documents can then be used to corroborate or refute the facts, thereby improving their overall quality.

Abstract: A query is defined that has an answer formed of terms from electronic documents. A repository having facts is examined to identify attributes corresponding to terms in the query. The electronic documents are examined to find other terms that commonly appear near the query terms. Hypothetical facts representing possible answers to the query are created based on the information identified in the fact repository and the commonly-appearing terms. These hypothetical facts are corroborated using the electronic documents to determine how many documents support each fact. Additionally, contextual clues in the documents are examined to determine whether the hypothetical facts can be expanded to include additional terms. A hypothetical fact that is supported by at least a certain number of documents, and is not contained within another fact with at least the same level of support, is presented as likely correct.

Abstract: A query is defined that has an answer formed of terms from electronic documents. A repository having facts is examined to identify attributes corresponding to terms in the query. The electronic documents are examined to find other terms that commonly appear near the query terms. Hypothetical facts representing possible answers to the query are created based on the information identified in the fact repository and the commonly-appearing terms. These hypothetical facts are corroborated using the electronic documents to determine how many documents support each fact. Additionally, contextual clues in the documents are examined to determine whether the hypothetical facts can be expanded to include additional terms. A hypothetical fact that is supported by at least a certain number of documents, and is not contained within another fact with at least the same level of support, is presented as likely correct.

Abstract: A system and method for extracting facts from documents. A fact is extracted from a first document. The attribute and value of the fact extracted from the first document are used as a seed attribute-value pair. A second document containing the seed attribute-value pair is analyzed to determine a contextual pattern used in the second document. The contextual pattern is used to extract other attribute-value pairs from the second document. The extracted attributes and values are stored as facts.

Abstract: A system, method, and computer program product for learning objects and facts from documents. Embodiments of the method comprise selecting a source object and a source document and identifying a title pattern and a contextual pattern based on the source object and the source document. A set of documents matching the title pattern and the contextual pattern are selected. For each document in the selected set, a name and one or more facts are identified by applying the title pattern and the contextual pattern to the document. Objects are identified or created based on the identified names and associated with the identified facts.

Abstract: A system and method for extracting facts from documents. A fact is extracted from a first document. The attribute and value of the fact extracted from the first document are used as a seed attribute-value pair. A second document containing the seed attribute-value pair is analyzed to determine a contextual pattern used in the second document. The contextual pattern is used to extract other attribute-value pairs from the second document. The extracted attributes and values are stored as facts.

Abstract: A system, method, and computer program product for learning objects and facts from documents. A source object and a source document are selected and a title pattern and a contextual pattern are identified based on the source object and the source document. A set of documents matching the title pattern and the contextual pattern are selected. For each document in the selected set, a name and one or more facts are identified by applying the title pattern and the contextual pattern to the document. Objects are identified or created based on the identified names and associated with the identified facts.

Abstract: Systems and methods for detecting fraudulent merchants using the content of orders completed by the merchants. A fraud detection engine of a fraud detection system generates a fraud detection model using feature data extracted from order content data for known fraudulent and known non-fraudulent merchants. The fraud detection engine executes the model using feature data extracted from order content data for a target merchant to determine a fraud risk associated with the target merchant. If the fraud risk of the merchant is indicative of a fraudulent merchant, the fraud detection system can issue a request to a fraud analyst to review the target merchant further. The results of the fraud analyst's review can be used to update the fraud detection model.

Abstract: A system, method, and computer program product for recognizing entity names from a plurality of documents. Embodiments of the methods comprise selecting a selection of documents from a plurality of documents, the selection of documents sharing a common pattern in their titles. The method further comprises determining a name candidate for each document in the selection by applying the common pattern to the title of the document, and matching the name candidates with a collection of entity names (the white list). Responsive to determining a match between the name candidates and the entity names in the white list, the method determines that the name candidates are valid entity names. In one embodiment, the name candidates are added to the white list after being determined to be valid entity names.

Abstract: A method and system of learning, or bootstrapping, facts from semi-structured text is described. Starting with a set of seed facts associated with an object, documents associated with the object are identified. The identified documents are checked to determine if each has at least a first predefined number of seed facts. If a document does have at least a first predefined number of seed facts, a contextual pattern associated with the seed facts is identified and other instances of content in the document matching the contextual pattern are identified. If the document includes at least a second predefined number of the other instances of content matching the contextual pattern, then facts may be extracted from the other instances.

Abstract: A system and method identifies a subject for a source document. The system and method identifies a collection of peer documents from the same domain as the source document. For each of the peer documents, a collection of linking documents containing a hyperlink to the peer document is identified. For each of the peer documents, a label is generated by choosing the longest-match anchor text of the linking documents. A pattern between the labels and the titles of the collection of peer documents is deduced. The subject of the source document is identified by applying the pattern to the title of the source document.

Abstract: A system and method identifies a subject for a source document. The system and method identifies a collection of peer documents from the same domain as the source document. For each of the peer documents, a collection of linking documents containing a hyperlink to the peer document is identified. For each of the peer documents, a label is generated by choosing the longest-match anchor text of the linking documents. A pattern between the labels and the titles of the collection of peer documents is deduced. The subject of the source document is identified by applying the pattern to the title of the source document.

Abstract: A system and method for extracting facts from documents. A fact is extracted from a first document. The attribute and value of the fact extracted from the first document are used as a seed attribute-value pair. A second document containing the seed attribute-value pair is analyzed to determine a contextual pattern used in the second document. The contextual pattern is used to extract other attribute-value pairs from the second document. The extracted attributes and values are stored as facts.