Abstract:
A computing device is described herein that is configured to select a subset of keywords from a plurality of keywords based at least on measures of competition associated with the keywords and to suggest the selected subset for bidding. The plurality of keywords is relevant to at least one advertising target. The computing device calculates a measure of competition for a respective keyword based on a number of bidders for the respective keyword and on a number of available advertisement slots in search results provided responsive to queries for the respective keyword.
Abstract:
A method and system for accessing a cellular mobile communication network, the method includes: after a terminal and a base station complete a ranging process, the terminal carrying out a basic capability negotiation with the base station, the base station and the terminal carrying out a WAPI access authentication process; and the terminal carrying out a subsequent access flow to access the cellular mobile communication network; wherein the WAPI access authentication process includes: the terminal sending an access authentication request packet, including a certificate and a signature of the terminal, to the base station; the base station authenticating the signature of the terminal, including the certificate into a certificate authentication request packet to send to an authentication server to perform validation; the base station sending an access authentication response packet to the terminal, and carrying out a unicast session key negotiation with the terminal to obtain a unicast session key.
Abstract:
Method for creating a graph representing web browsing behavior, including receiving web browsing behavior data from one or more web browsers; adding a node on the graph for each web page listed in the web browsing behavior data; adding a first link connecting two or more nodes on the graph, wherein the first link representing a hyperlink for accessing a webpage; calculating an amount of time in which each web page is being accessed; determining a number of units of time in the calculated amount of time; adding one or more virtual nodes to the graph based on the number of units of time; and adding a second link connecting two or more virtual nodes on the graph, wherein the second link representing a virtual hyperlink for accessing a webpage.
Abstract:
Some implementations provide techniques for estimating impression numbers. For example, a log of advertisement bidding data may be used to generate and train an impression estimation model. In some implementations, an impression estimation component may use a boost regression technique to determine a predicted impression value range based on a proposed bid received from an advertiser. For example, the predicted impression value range may be determined based on a predicted estimation error. Additionally, in some instances, the predicted impression value range may be evaluated using one or more evaluation metrics.
Abstract:
Some implementations generate a mapping function using one or more historic performance indicators for a set of ad-keyword pairs and one or more advertisement metrics extracted from the set of ad-keyword pairs. The mapping function may be applied to map one or more advertisement metrics of a particular ad-keyword pair to determine a quality score for the particular ad-keyword pair. For example, the quality score may be used when determining whether to select an advertisement for display or may be provided as feedback to an advertiser. Additionally, in some implementations, the mapping function may be applied to determine a quality score for a new ad-keyword pair that has not yet accumulated historic information.
Abstract:
Many search engines attempt to understand and predict a user's search intent after the submission of search queries. Predicting search intent allows search engines to tailor search results to particular information needs of the user. Unfortunately, current techniques passively predict search intent after a query is submitted. Accordingly, one or more systems and/or techniques for actively predicting search intent from user browsing behavior data are disclosed herein. For example, search patterns of a user browsing a web page and shortly thereafter performing a query may be extracted from user browsing behavior. Queries within the search patterns may be ranked based upon a search trigger likelihood that content of the web page motivated the user to perform the query. In this way, query suggestions having a high search trigger likelihood and a diverse range of topics may be generated and/or presented to users of the web page.
Abstract:
An anti-spam tool works with a web browser to detect spam webpages locally on a client machine. The anti-spam tool can be implemented either as a plug-in module or an integral part of the browser, and manifested as a toolbar. The tool can perform an anti-spam action whenever a webpage is accessed through the browser, and does not require direct involvement of a search engine. A spam detection module installed on the computing device determines whether a webpage being accessed or whether a link contained in the webpage being accessed is spam, by comparing the URL of the webpage or the link with a spam list. The spam list can be downloaded from a remote search engine server, stored locally and updated from time to time. A two-level indexing technique is also introduced to improve the efficiency of the anti-spam tool's use of the spam list.
Abstract:
The page ranking technique described herein employs a Markov Skeleton Mirror Process (MSMP), which is a particular case of Markov Skeleton Processes, to model and calculate page importance scores. Given a web graph and its metadata, the technique builds an MSMP model on the web graph. It first estimates the stationary distribution of a EMC and views it as transition probability. It next computes the mean staying time using the metadata. Finally, it calculates the product of transition probability and mean staying time, which is actually the stationary distribution of MSMP. This is regarded as page importance.
Abstract:
A method of processing an external service request in a storage area network (SAN) is used for responding a service request in the SAN with multiple controllers, and the method includes the following steps. A first controller of the SAN receives a request packet of an external network. When the first controller determines that the request packet must be transmitted to a second controller actually providing service in an internal network, the request packet is transmitted to the second controller. The second controller receives the request packet, and parses a source address contained therein for recording. The second controller executes an operation instruction corresponding to the request packet, and then generates an acknowledge packet. The second controller takes the source address as a destination address of the acknowledge packet and directly transmits the acknowledge packet to an original request initiator.
Abstract:
An anti-spam technique for protecting search engine ranking is based on mining search engine optimization (SEO) forums. The anti-spam technique collects webpages such as SEO forum posts from a list of suspect spam websites, and extracts suspicious link exchange URLs and corresponding link formation from the collected webpages. A search engine ranking penalty is then applied to the suspicious link exchange URLs. The penalty is at least partially determined by the link information associated with the respective suspicious link exchange URL. To detect more suspicious link exchange URLs, the technique may propagate one or more levels from a seed set of suspicious link exchange URLs generated by mining SEO forums.