7239 results about "Degree of similarity" patented technology

A method and computer readable medium for exploring similar users and items of a media service. In one aspect, a user can explore for similar users iteratively. In one aspect, a user interface is generated that displays a user selectable indicia representing a similar member function for allowing a user to search a media service for at least one other user which has a degree of similarity with respect to the searching user. In another aspect, a method facilitates the search of such a similar user within a media service.

A method, a device and computer program products for protecting privacy of users from web-trackers

The method comprising:

• • capturing and removing a public unique identifier set by a Website (300) in a computing device (100D) of a user (100);
  • monitoring, during a first time-period, web-requests the user (100) makes to obtain a web-behavioral profile of the user (300), and storing the obtained web-behavioral profile as a first vector;
  • tracking, during a second time-period, the web-requests to examine the effect each web-request has on assisting the de-anonymization of the user (100), obtaining a second vector;
  • classifying, the obtained second vector taking into account a computed similarity score parameter;
  • creating and mapping, a corresponding private unique identifier for said captured public identifier; and
  • executing, based on said mapping between the private and the public unique identifiers, an intervention algorithm for said web-tracker, that considers a configured intervention policy.

Systems and methods for analyzing electronic messages are disclosed. In some embodiments, the method comprises receiving a new received message from an indicated sender, the new received message having a first message characteristic of the indicated sender and a second message characteristic, identifying an actual sender message characteristic pattern of an actual sender using the first message characteristic, probabilistically comparing the second message characteristic to the actual sender message characteristic pattern, determining a degree of similarity of the second message characteristic to the actual sender message characteristic pattern, and influencing a probability that the indicated sender is the actual sender based upon the degree of similarity. There may be multiple message characteristics and patterns. In some embodiments, the methods may utilize pattern matching techniques, recipient background information, quality measures, threat intelligence data or URL information to help determine whether the new received message is from the actual sender.

Techniques for controlling distribution of information from a secure domain by automatically detecting outgoing messages which violate security policies corresponding to the secure domain. Semantic models are constructed for one or more message categories and for the outgoing messages. The semantic model of an outgoing message is compared with the semantic models of the message categories to determine a degree of similarity between the semantic models. The outgoing message is classified based on the degree of similarity obtained from the comparison. A determination is made, based on the classification of the outgoing message, if distribution of the outgoing message would violate a security policy for the secure domain. Distribution of the outgoing message is allowed if no security policy is violated.

The aural similarity measuring system and method provides a measure of the aural similarity between a target text (10) and one or more reference texts (11). Both the target text (10) and the reference texts (11) are converted into a string of phonemes (15) and then one or other of the phoneme strings are adjusted (16) so that both are equal in length. The phoneme strings are compared (12) and a score generated representative of the degree of similarity of the two phoneme strings. Finally, where there is a plurality of reference texts the similarity scores for each of the reference texts are ranked (13). With this aural similarity measuring system the analysis is automated thereby reducing risks of errors and omissions. Moreover, the system provides an objective measure of aural similarity enabling consistency of comparison in results and reproducibility of results.

Methods and apparatus, including computer program products, for identifying matches between disparate schemas calculates a degree of similarity between elements of two schemas using each of multiple matching processes. The calculated degrees of similarity are combined using a first weighting vector to produce first combined degrees of similarity. The first weighting vector includes multiple weighting coefficients and each weighting coefficient corresponds to one of the matching processes. The weighting coefficients are tuned using information relating to a predicted degree of matching accuracy associated with the first weighting vector.

Techniques for improving detection of watermarks in content that has undergone a lossy transformation. One of the techniques is used when the message that is contained in a watermark belonging to a digital representation that is derived from an original watermarked digital representation cannot be decoded. The technique obtains information about the watermark by comparing the watermark vector for the watermark that cannot be decoded with a replica of the watermark vector from the original watermarked digital representation. The replica is made using the message. Depending on the degree of similarity, the watermark's presence and some of its characteristics may be determined. Another technique improves the robustness of watermarks that are used for authentication by employing a short (even single-bit) watermark vector to make the watermark and using the message needed for the authentication to determine where the watermark is located in the digital representation. Authentication of a digital representation is done by determining whether the watermark is present in the digital representation. In another technique, detection of the presence of a watermark is used to determine what areas of a digital representation have been subject to alteration. Techniques for synchronizing digital representations for watermark detection and other purposes include adding marks whose locations can be automatically detected only with the help of information that is external to the digital representation, such as a key, and adding marks to a sequence of digital representations and detecting the marks by summing the sequence.

An environment identifying apparatus (400) is adapted to be mounted in a robot apparatus that moves in an identifiable unique environment in which a plurality of landmarks are located so as to identify the current environment by means of a plurality of registered environments. The environment identifying apparatus comprises an environment map building section (402) for recognizing the landmarks in the current environment, computing the movement/state quantity of the robot apparatus itself and building an environment map of the current environment containing information on the positions of the landmarks in the current environment on the basis of the landmarks and the movement/state quantity, an environment map storage section (403) having a data base of registered environment maps containing positional information on the landmarks and environment IDs, an environment identifying section (404) for identifying the current environment on the basis of the degree of similarity between the environment map of the current environment and each of the registered environment maps and an environment exploring section (405) for exploring a new environment.

The embodiment of the invention provides a human face similarity matching method which comprises the following steps of: obtaining a first human face image; extracting the feature data of a plurality of key points in the first human face image and a stored second human face image; searching a matched key point in the key points of the second human face image for each key point of the first human face image; calculating the score of the similarity between the key point of the first human face image and the key point of the second human face image matching with the key point of the first human face image; and inosculating each key point of the first human face image with the similarity score of the key point of the second human face image to judge whether the two are matched with each other.

The invention discloses a Chinese question-answering system based on a neural network, which comprises a user interface module, a question word pre-segmentation module, a nerve cell pre-tagging module, a learning and training module, a nerve cell knowledge base module, a semantic block identification module, a question set index module and an answer reasoning module. The system comprises the steps of: firstly adopting an SIE encoding mode to encode the in-vocabulary words of the semantic block according to corresponding position, later converting an identification problem of the question semantic block into a tagging classification problem, and then adopting a classification model based on the neural network to determine the semantic structure of the question, and finally combing the semantic structure of the question to realize the question similarity computation based on the neural network and comparing the weight of various semantic features of the question by extracting the tagged semantic features of the question, thereby providing a basis for final answer reasoning. The Chinese question-answering system integrates the syntax, the semantics and the contextual knowledge of the question and can simulate the process that human beings process the sentence.

First similarity values along at least four directions are ascertained within a local area containing a target pixel and weighted averaging is performed by adding the pixel values of pixels around the target pixel value to the pixel value of the target pixel, adding weight along a direction having a small first similarity value (along a direction manifesting a high degree of similarity). By incorporating the pixel value level differences among a plurality of pixels on adjacent lines extending adjacent to the target pixel into the first similarity values, it becomes possible to effectively remove jaggies that are difficult to eliminate in the prior art. Furthermore, by making a judgment on degrees of similarity by incorporating color information such as characteristics differences among different color pixels, a more accurate judgment can be made with regard to the image structure to enable very accurate direction-dependent low-pass filtering.

A method and apparatus for real-time tracking of a non-rigid target. The tracking is based on visual features, such as color and/or texture, where statistical distributions of those features characterize the target. A degree of similarity (rho(y0)) is computed between a given target (at y0) in a first frame and a candidate target (at y1) in a successive frame, the degree being expressed by a metric derived from the Bhattacharyya coefficient. A gradient vector corresponding to a maximization of the Bhattacharyya coefficient is used to derive the most probable location of the candidate target in the successive frame.

A system and method are provided for eliciting interesting structure from a collection of entities or resources with explicit and/or implicit, static and/or dynamic relations, called “affinities,” between them. Interesting structure includes (1) notions of quality, authority, or definitiveness of information, (2) notions of relevance to a user's information need, (3) notions of similarity among the plurality of resources retrieved from a universe of resources by a query process, and (4) notions of similarity among the usages of resources by different users/servers. Similarities between entities are computed, based on similarities between the affinity values for the entities. That is, where the affinitiy values for two entities resemble each other, the two entities have a high degree of similarity. Using the similarities, the entities are ranked, clustered, etc., based on a significance derived from the similarities. The ranking, clustering, etc., makes up the interesting structure which is sought.

Embodiments include a method, apparatus, program, and system for distributing data items among a plurality of data storage units, the data items being an aggregation of data from a plurality of data sources. The method comprises generating a semantic description of each of the plurality of data sources; calculating, for each pair of data sources from among the plurality of data sources, a degree of similarity between the semantic descriptions of the pair of data sources; and allocating data items to data storage units in dependence upon the calculated degree of similarity between the data source of a data item being allocated and the or each data source of data items already allocated to the data storage units.

The invention discloses a calculating method of text similarity degree and vocabulary meaning similarity degree and system and application system, which comprises the following steps: basing on vocabulary data bank; proceeding initialize; calculating; getting initial vocabulary meaning similarity degree among vocabulary in the vocabulary data bank; basing on the initial vocabulary meaning similarity degree; calculating initial semantic similarity degree among text; iterating semantic similarity degree among each text and vocabulary meaning similarity degree among vocabulary till constriction; constructuring final vocabulary meaning similar matrix with final vocabulary similarity degree; transforming the text vocabulary frequency vector of the initial text to the new text vocabulary text vocabulary frequency vector; calculating text similarity degree in the text collection. This invention can improve related property of current text especially about short text.

Method, article, apparatus and computer system facilitating the easy and intuitive inputting of a desired graphical object into an electronic system from a large plurality of predetermined graphical objects. In one example embodiment, this is achieved by assigning each of said graphical objects into one of a plurality of groups in accordance with a predetermined similarity criterion, associating respective base shapes to each of said groups, wherein said base shapes having a certain degree of similarity to the objects assigned to the associated group according to said similarity criterion and associating in each of said groups at least one gesture to each of said graphical objects, so that the associated gestures are distinguishable from each other. In order to input the desired graphical object, one of the groups is selected by selecting its base shape and then the desired graphical object is identified by drawing the respective gesture associated thereto.

A database of visual images includes metadata having, for a particular image, at least one entry specifying: a part of that image, another stored image, and a measure S_abi of the degree of similarity between that specified part and the specified other image. The searching method comprises displaying one or more images; receiving input from a user (for example by using a gaze tracker) indicative of part of the displayed images; determining measures of interest for each of a plurality of non-displayed stored images specified by the metadata for the displayed image(s), as a function of the similarity measure(s) and the relationship between the user input and the part specified; and, on the basis of these measures, selecting, from those non-displayed stored images, further images for display.

A technique for determining when documents stored in digital format in a data processing system are similar. A method compares a sparse representation of two or more documents by breaking the documents into “chunks” of data of predefined sizes. Selected subsets of the chunks are determined as being representative of data in the documents and coefficients are developed to represent such chunks. Coefficients are then combined into coefficient clusters containing coefficients that are similar according to a predetermined similarity metric. The degree of similarity between documents is then evaluated by counting clusters into which chunks of similar documents fall.

The invention discloses a commendation method of personalized resource information based on scene information. The method comprises: pre-processing the web page of a synergic labeling system, storing the information of all labeling behaviors of a user according to the information of the labeling behaviors, wherein the information is extruded by a specific user and comprises labeled resource information, used tag information and labeled time information; generating grading data expressing user preferences according to the tag information that the user uses the resources in a database and the time information of the labeled resource; calculating the similarity among users based on the generated grading data expressing the user preference so as to determine that the users with similar interest are adjacent; commending the resource that is not labeled by the user to the users according to the adjacent preference information of the users to complete the commendation of synergic filtrated personalized resource. Experiments show that better personalized commendation service can be provided for the users through integrating the scene information.

In order to acquire a suitable fingerprint image by correcting an elongated fingerprint image, a line sensor acquires fingerprint image as a plurality of line-shaped images. A computation unit computes a similarity value by use of an evaluation function for evaluating the degree of similarity between the line-shaped images. The similarity value represents the degree of similarity between a first line-shaped image and a second line-shaped image which serve as a similarity evaluation target and are included in the plurality of the line-shaped image. A compression unit compresses the first line-shaped image and the second line-shaped image when the similarity value is equal to or larger than a predetermined threshold value to generate a new line-shaped image. A generation unit generates the entire fingerprint image by combining the new line-shaped image with the other line-shaped images.

The invention relates to a realization method and system for electronic medical record post-structuring and auxiliary diagnosis. A combination mode of multiple types of distance measurement is used: a character string editing distance refers to a minimum number of replacement, insertion and deletion operations required for converting a character into another character string; a Jaro-Winkler distance measures similarity between two character strings and is used for repeated recording detection; a geometric mean value of a Chinese character distance and a Chinese character input method is adopted as comprehensive similarity measurement for measuring similarity between characteristic texts; characteristic ranking is realized by using a TF-IDF method and is used for assessing the importance of characteristic terms relative to documents in a file set or a corpus library, and the importance of the characteristic terms is in direct proportion to an occurrence frequency in the documents and is in inverse proportion to an occurrence document in the corpus library; and files are converted to be in a file format of PU learning of a positive example data set and an unlabelled data set according to the generated characteristic terms, and through the PU learning, the system automatically recommends related diagnoses for clinical medical personnel to refer.

An organization's data records are often noisy: because of transcription errors, incomplete information, and lack of standard formats for textual data. A fundamental task during data cleansing and integration is matching strings—perhaps across multiple relations—that refer to the same entity (e.g., organization name or address). Furthermore, it is desirable to perform this matching within an RDBMS, which is where the data is likely to reside. In this paper, We adapt the widely used and established cosine similarity metric from the information retrieval field to the relational database context in order to identify potential string matches across relations. We then use this similarity metric to characterize this key aspect of data cleansing and integration as a join between relations on textual attributes, where the similarity of matches exceeds a specified threshold. Computing an exact answer to the text join can be expensive. For query processing efficiency, we propose an approximate, sampling-based approach to the join problem that can be easily and efficiently executed in a standard, unmodified RDBMS. Therefore the present invention includes a system for string matching across multiple relations in a relational database management system comprising generating a set of strings from a set of characters, decomposing each string into a subset of tokens, establishing at least two relations within the strings, establishing a similarity threshold for the relations, sampling the at least two relations, correlating the relations for the similarity threshold and returning all of the tokens which meet the criteria of the similarity threshold.

Coreference resolution is the process of identifying when two noun phrases (NP) refer to the same entity. Two main contributions to computational coreference resolution are made. First, this work contributes a new method for recognizing when an NP is anaphoric. Second, traditional approaches to coreference resolution typically select the most appropriate antecedent by recognizing word similarity, proximity, and agreement in number, gender, and semantic class. This work contributes a new source of evidence that focuses on the roles that an anaphor and antecedent play in particular events or relationships. I show that using contextual role knowledge as part of the coreference resolution process increases the number of anaphors that can be resolved, and I demonstrate an unsupervised method for acquiring contextual role knowledge that does not require an annotated training corpus. A probabilistic model based on the Dempster-Shafer model of evidence is used to incorporate contextual role knowledge with traditional evidence sources.

The application presents a question and answer recommendation method based on artificial intelligence, a question and answer recommendation device and a computer device. The question and answer recommendation method based on artificial intelligence includes steps of receiving search terms input by a user, wherein the search terms are questions; matching the search terms with questions having answers in a question and answer knowledge base; if the terms in question and answer knowledge base are not matched with the search terms completely, calculating the semantic similarity between the search terms and the questions having answers in the question and answer knowledge base; judging if the question and answer knowledge base has a question of which semantic similarity with the search terms is larger than a preset threshold value; if it does, using the answer of which semantic similarity with the search terms is more than the preset threshold value as the answer of the search term, and recommending to a user. Answer recommendation is realized according to the semantic similarity, thus the meaning transfer risk is reduced and the interference by meaningless oral expression element is reduced.

An image processing method for selecting a subset of n (where n is two or more) images representative of a test set of images comprises the step of: detecting a degree of similarity between images in the test set of images, so that the subset of images comprises those n images having substantially the lowest similarity with other images in the set.