238 results about "Link analysis" patented technology

Fraud detection is facilitated by developing account cluster membership rules and converting them to database queries via an examination of clusters of linked accounts abstracted from the customer database. The cluster membership rules are based upon certain observed data patterns associated with potentially fraudulent activity. In one embodiment, account clusters are grouped around behavior patterns exhibited by imposters. The system then identifies those clusters exhibiting a high probability of fraud and builds cluster membership rules for identifying subsequent accounts that match those rules. The rules are designed to define the parameters of the identified clusters. When the rules are deployed in a transaction blocking system, when a rule pertaining to an identified fraudulent cluster is triggered, the transaction blocking system blocks the transaction with respect to new users who enter the website.

An implicit links enhancement system and method for search engines that generates implicit links obtained from mining user access logs to facilitate enhanced local searching of web sites and intranets. The implicit links search enhancement system and method includes extracting implicit links by mining users' access patterns and then using a modified link analysis algorithm to re-rank search results obtained from traditional search engines. More specifically, the implicit links search enhancement method includes extracting implicit links from a user access log, generating an implicit links graph from the extracted implicit links, and computing page rankings using the implicit links graph. The implicit links are extracted from the log using a two-item sequential pattern mining technique. Search results obtained from a search engine are re-ranked based on an implicit links analysis performed using an updated implicit links graph, a modified re-ranking formula, and at least one re-ranking technique.

Methods and systems are provided for identifying on-topic sources of media content. According to one embodiment, candidate seed sites are identified from which current seeds are selected for deep crawling. The current seeds are identified by correlating relevancy scores or key-word search results from multiple search engines; and selecting the current seeds based on on-topic scores of the candidate seeds. Periodically, a topic net associated with the topic area of interest is executed to locate relevant sources of media content by (i) building a graph in which nodes represent pages and edges represent links among pages by performing an iterative 360 crawl starting from the seeds; (ii) assigning initial node graph scores; (iii) computing final node graph scores by performing link analysis; (iv) computing a site graph scores by aggregating and averaging corresponding node graph scores; and (v) configuring sites with the highest site graph scores to be scraped.

A method, apparatus, and computer program product for a personal search engine that includes a hybrid web composed of: the similarity web, and directed hyperlinks. Components include a parser (extracting words from documents); a text relevance analyzer; a link analysis method; the similarity web; a similarity analyzer; and hyperlinks. Other components include a navigation window; and FQSs. The combination of all the above may be incorporated into a working personal search engine.

Techniques for providing protection against unsafe links on a social networking website are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for providing protection against unsafe links on a social networking website comprising: receiving, from the social networking website, user profile data associated with a user of the social networking website, scanning, from the user profile data, a plurality of links, accessing a safety rating for each of the plurality of links, and outputting, to a client device associated with the user, a link analysis report that indicates the safety rating of one or more of the plurality of links.

A comprehensive scheme to detect phishing emails using features that are invariant and fundamentally characterize phishing. Multiple embodiments are described herein based on combinations of text analysis, header analysis, and link analysis, and these embodiments operate between a user's mail transfer agent (MTA) and mail user agent (MUA). The inventive embodiment, PhishNet-NLP™, utilizes natural language techniques along with all information present in an email, namely the header, links, and text in the body. The inventive embodiment, PhishSnag™, uses information extracted form the embedded links in the email and the email headers to detect phishing. The inventive embodiment, Phish-Sem™ uses natural language processing and statistical analysis on the body of labeled phishing and non-phishing emails to design four variants of an email-body-text only classifier. The inventive scheme is designed to detect phishing at the email level.

The disclosed embodiments fulfill searches and determine the validity of a large set of noisy facts and rank the set of facts according to a validity score. Embodiments construct a fact graph by linking together facts that share a common relation structure and entity or instance of an argument. Facts are re-ranked and validated using link analysis processes which propagate weight (validity/authority) through the fact graph. The resulting weights for each fact are potentially combined with other scores (such as from fact extraction algorithms) in order to come up with a final ranking of the facts.

A device, computer program product and a method for searching, navigating or retrieving documents in a set of electronic documents, including performing a link analysis of the set of electronic documents. The link analysis includes one of analyzing at least two of the set of documents with at least a portion of a similarity graph constructed among the set of documents and analyzing the at least two of the set of documents with the at least a portion of the similarity graph and at least a portion of a hyperlink graph constructed from hyperlinks between the set of documents. Also described is a method for building a similarity matrix.

A flexible and extensible architecture allows for secure searching across an enterprise. Such an architecture can provide a simple Internet-like search experience to users searching secure content inside (and outside) the enterprise. The architecture allows for the crawling and searching of a variety or sources across an enterprise, regardless of whether any of these sources conform to a conventional user role model. The architecture further allows for security attributes to be submitted at query time, for example, in order to provide real-time secure access to enterprise resources. The user query also can be transformed to provide for dynamic querying that provides for a more current result list than can be obtained for static queries.

The present invention relates to a system and method for performing vehicle onboard analysis on the data associated with the vehicle and implementing a cloud-based distributed data stream mining algorithm for detecting patterns from vehicle diagnostic and correlating the pattern with the contextual data. The system applies the distributed data mining algorithms for mining the results of the vehicle onboard analytics sent over the wireless network to the server and correlates the analyzed data with the contextual data of the vehicle. The system extracts performance patterns from data, builds predictive models from vehicle diagnostic, and correlates the predicted model with the business process using state of the art link analysis techniques.

The invention relates to a topic crawler system based on social labels, which comprises a page acquisition module, a page processing module, a correlation calculation module, a storage module, a link extraction module and a link analysis module. The system makes full use of the social labels of web pages, utilizes the properties that the social labels are the acknowledged description on page contents and are closer to actual contents described by the web pages to judge the correlation of the web pages, and applies the correlation to a network topic crawler to guide the crawling direction of the crawler and provide high-quality webpage data contents for a topic search engine. The system well uses the network bandwidth resources to reduce unnecessary expenditure during web page acquisition, adopts different storage modes aiming at different requirements to reduce the consumption of IO, and adopts a multi-level cache mechanism to reduce blockage and improve the efficiency of the crawler. Under the support of the social labels, the system optimizes a crawler framework, and provides an optimal webpage data set for subsequent other processing flows of the topic search engine.

The invention discloses a short text characteristic expanding method based on a semantic atlas. The method includes the steps: performing subject modeling by the aid of a training data set of a short text, and extracting subject term distribution; reordering the subject term distribution; building a candidate keyword dictionary and a subject-keyword semantic atlas; calculating comprehensive similarity degree evaluation of candidate keywords and seed keywords based on a link analysis method, and selecting the most similar candidate keywords to finish expanding the short text. Compared with a short text characteristic representation method based on a language model, the method is simple to operate and high in execution efficiency, and semantic correlation information between the keywords is sufficiently used. Compared with a traditional short text characteristic representation method based on a word bag model, the problems of data sparseness and semantic sensitivity are effectively relieved, and the method is independent of external large-scale auxiliary training corpus or a search engine.

The invention provides a method for constructing a topic web crawler system, which comprises the following steps of: (1) defining an initial description vector of a topic, setting an initial threshold value of the correlation degree and initializing a URL (Uniform Resource Locator) queue; (2) sequentially acquiring URLs from the initial URL queue to carry out crawl; (3) carrying out text analysis on the URLs; (4) carrying out link analysis on the URLs; (5) calculating the correlation degrees of the URLs with the topic; (6) adding the URLs of which the correlation degrees are more than the threshold value of the correlation degree into an ordered URL queue, sorting the URLs according to the correlation degrees of the URLs with the topic vector, carrying out crawl sequentially until the queue is empty, extracting a sub URL in each crawled webpage, and returning the step (3); (7) carrying out optimization of a genetic algorithm by using the genetic algorithm; and (8) updating the topic vector by a Rocchio feedback module, dynamically regulating the threshold value of the correlaton degree and continously crawling the webpages. In the method, a great amount of training texts do not need to be prepared in advance. The method has high speed and is suitable for processing an immense amount of on-line webpage data.

The invention relates to a flow scheduling system and method based on SDN. The method comprises the following steps: acquiring a network link parameter configured by a user; starting routing collection and flow collection processes; performing link analysis; judging whether a congested link exists, if so, scheduling the flow of the congested link to an idle link by a flow scheduling module, and otherwise, continuing to perform periodic link analysis. By adoption of the system and the method, being different from the system under distributed architecture, the flow scheduling method and system based on the SDN can comprehensively sense the link congestion or link faults; the network link heath condition updated in real time can be converted to a network link metric coefficient, and thus the selection of an optimal path is more accurate; and in the case of network link congestion, the flow scheduling method and system based on the SDN provided by the invention are started to quickly and effectively eliminate the link congestion, and the links are reasonably configured to maximize the bandwidth utilization rate, and flow load balance of the whole network can be realized.

A method, device, and computer program product for ranking documents using link analysis, with remedies for sinks, including forming a metagraph from an original graph containing a link and a node; and one of reversing a link in the metagraph, and pumping a source in the metagraph.

The invention relates to a topic information acquisition method based on network topology. An initial web page set is obtained from a search engine and is expressed as a vector set through purification, word division and removal of stop words, and a vector space model is used to calculate the text similarity. A network structure is utilized to perform linkage analysis to extracted URLs first, the linkage is filtered through directory hierarchies of the URLs, and then the weights of the URLs are modified according to the scaleless property of a network to perform the prior absorption selection. At the same time, unrelated topic areas are feedback, and the lengths of buffer areas of unrelated URLs are set through the distance between the URLs and a seed set. The heat of acquired topics is calculated to select one topic to obtain a new reply.

The invention discloses a method for implementing a topical crawler system based on learning URL string information. First, a traditional correlation judgment method of the topical crawler is improved, and a method for judging the correlation between a target URL and a topic based on URL string information, web content, and anchor information is proposed. Information brought by the URL string is learned continuously by adopting a method of machine learning to update relevant vectors of the topic dynamically, and the judgment accuracy of correlation between the target URL and the topic is improved. Finally, a crawler strategy which combines content analysis and link analysis is adopted while computational complexity is not increased, which prevents the topical crawler from trapping in local optimum, improves overallness of the crawler when crawling, and improves efficiency of the crawler. The method of the invention can be used in a crawler module of a vertical search engine to crawl web pages of a particular field.

The information set importance determination system of the present invention includes a page information management unit for managing an attribute of page information constituting hyper-media information, a ink information management unit for holding and managing linkage between page information, data take-in device for registering hyper-media information in the page information management unit and the link information management unit, a page analysis unit for determining an importance of each page, a link analysis unit for determining a weight of each link based on link information, and a page set sorting unit for sorting a page set based on a page importance of each page.