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1850 results about "Pattern matching" patented technology

In computer science, pattern matching is the act of checking a given sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact: "either it will or will not be a match." The patterns generally have the form of either sequences or tree structures. Uses of pattern matching include outputting the locations (if any) of a pattern within a token sequence, to output some component of the matched pattern, and to substitute the matching pattern with some other token sequence (i.e., search and replace).

Face detecting camera and method

A method for determining the presence of a face from image data includes a face detection algorithm having two separate algorithmic steps: a first step of prescreening image data with a first component of the algorithm to find one or more face candidate regions of the image based on a comparison between facial shape models and facial probabilities assigned to image pixels within the region; and a second step of operating on the face candidate regions with a second component of the algorithm using a pattern matching technique to examine each face candidate region of the image and thereby confirm a facial presence in the region, whereby the combination of these components provides higher performance in terms of detection levels than either component individually. In a camera implementation, a digital camera includes an algorithm memory for storing an algorithm comprised of the aforementioned first and second components and an electronic processing section for processing the image data together with the algorithm for determining the presence of one or more faces in the scene. Facial data indicating the presence of faces may be used to control, e.g., exposure parameters of the capture of an image, or to produce processed image data that relates, e.g., color balance, to the presence of faces in the image, or the facial data may be stored together with the image data on a storage medium.

Advanced information gathering for targeted activities

An agent based system assists in preparing an individual for an upcoming meeting by helping him / her retrieve relevant information about the meeting from various sources based on preexisting information in the system. The system obtains input text in character form indicative of the target meeting from a calendar program that includes the time of the meeting. As the time of the meeting approaches, the calendar program is queried to obtain the text of the target event and that information is utilized as input to the agent system. Then, the agent system parses the input meeting text to extract its various components such as title, body, participants, location, time etc. The system also performs pattern matching to identify particular meeting fields in a meeting text. This information is utilized to query various sources of information on the web and obtain relevant stories about the current meeting to send back to the calendaring system. For example, if an individual has a meeting with Netscape and Microsoft to talk about their disputes, the system obtains this initial information from the calendaring system. It will then parse out the text to realize that the companies in the meeting are “Netscape” and “Microsoft” and the topic is “disputes”. It will then surf the web for relevant information concerning the topic. Thus, in accordance with an objective of the invention, the system updates the calendaring system and eventually the user with the best information it can gather to prepare for the target meeting. In accordance with a preferred embodiment, the information is stored in a file that is obtained via selection from a link imbedded in the calendar system.

System, method and program product for answering questions using a search engine

The present invention is a system, method, and program product that comprises a computer with a collection of documents to be searched. The documents contain free form (natural language) text. We define a set of labels called QA-Tokens, which function as abstractions of phrases or question-types. We define a pattern file, which consists of a number of pattern records, each of which has a question template, an associated question word pattern, and an associated set of QA-Tokens. We describe a query-analysis process which receives a query as input and matches it to one or more of the question templates, where a priority algorithm determines which match is used if there is more than one. The query-analysis process then replaces the associated question word pattern in the matching query with the associated set of QA-Tokens, and possibly some other words. This results in a processed query having some combination of original query tokens, new tokens from the pattern file, and QA-Tokens, possibly with weights. We describe a pattern-matching process that identifies patterns of text in the document collection and augments the location with corresponding QA-Tokens. We define a text index data structure which is an inverted list of the locations of all of the words in the document collection, together with the locations of all of the augmented QA-Tokens. A search process then matches the processed query against a window of a user-selected number of sentences that is slid across the document texts. A hit-list of top-scoring windows is returned to the user.

Systems and Methods for Isolating On-Screen Textual Data

The systems and methods of the client agent describe herein provides a solution to obtaining, recognizing and taking an action on text displayed by an application that is performed in a non-intrusive and application agnostic manner. In response to detecting idle activity of a cursor on the screen, the client agent captures a portion of the screen relative to the position of the cursor. The portion of the screen may include a textual element having text, such as a telephone number or other contact information. The client agent calculates a desired or predetermined scanning area based on the default fonts and screen resolution as well as the cursor position. The client agent performs optical character recognition on the captured image to determine any recognized text. By performing pattern matching on the recognized text, the client agent determines if the text has a format or content matching a desired pattern, such as phone number. In response to determining the recognized text corresponds to a desired pattern, the client agent displays a user interface element on the screen near the recognized text. The user interface element may be displayed as an overlay or superimposed to the textual element such that it seamlessly appears integrated with the application. The user interface element is selectable to take an action associated with the recognized text.
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