Abstract: Described is a technology by which uploaded GPS data is indexed according to spatio-temporal relationships to facilitate efficient insertion and retrieval. The indexes may be converted to significantly smaller-sized data structures when new updates to that structure are not likely. GPS data is processed into a track of spatially-partitioned segments such that each segment has a cell. Each cell has an associated temporal index (a compressed start-end tree), into which data for that cell's segments are inserted. The temporal index may include an end time index that relates each segment's end time to a matching start time index. Given query input comprising a spatial predicate and a temporal predicate, tracks may be searched for by determining which spatial candidate cells may contain matching results. For each candidate cell, the search accesses the cell's associated temporal index to find any track or tracks that correspond to the temporal predicate.

Abstract: A method and system for generating a search result for a query of hierarchically organized documents based on retrieval of subtrees that are key resources for topic distillation is provided. The retrieval system may identify documents relevant to a query using conventional searching techniques. The retrieval system then calculates a subtree feature for subtrees that have an identified document as their root. After the retrieval system calculates the subtree feature for the subtrees, the retrieval system may generate a subtree relevance score for each subtree based on its subtree feature. The retrieval system may then order the identified documents based on their corresponding subtree relevances.

Abstract: A method and system for ranking objects of different object types based on their popularity is provided. A ranking system calculates the popularity of objects based on relationships between the objects. A relationship indicates how one object is related to another object. Thus, objects of one object type may have one or more relationships with objects of another object type. One goal of the ranking system is to rank the objects of the different object types based on their popularity. The objects and their relationships can be represented using a graph with nodes representing objects and links representing relationships between objects. The ranking system assigns a popularity propagation factor to each relationship to represent its contribution to the popularity of objects of that type.

Abstract: A method and system for identifying locations associated with a web resource is provided. The location system identifies three different types of geographic locations: a provider location, a content location, and a serving location. A provider location identifies the geographic location of the entity that provides the web resource. A content location identifies the geographic location that is the subject of the web resource. A serving location identifies the geographic scope that the web page reaches. An application can select to use the type of location that is of particular interest.

Abstract: A method and system for prioritizing communications based on classifications of sentences within the communications is provided. A sentence classification system may classify sentences of communications according to various classifications such as “sentence mode.” The sentence classification system trains a sentence classifier using training data and then classifies sentences using the trained sentence classifier. After the sentences of a communication are classified, a document ranking system may generate a rank for the communication based on the classifications of the sentences within the communication. The document ranking system trains a document rank classifier using training data and then calculates the rank of communications using the trained document rank classifier.

Abstract: A summary system for evaluating summaries of documents and for generating summaries of documents based on normalized probabilities of portions of the document. A summarization system generates a summary by selecting sentences for the summary based on their normalized probabilities as derived from a document model. An evaluation system evaluates the effectiveness of a summary based on a normalized probability for the summary that is derived from a document model.

Abstract: A relevance system determines the relevance of a query term to a document based on spans within the document that contain the query term. The relevance system aggregates the relevance of the query terms into an overall relevance for the document. For each query term, the relevance system calculates a span relevance for each span that contains that query term. The relevance system then aggregates the span relevances for a query term into a query term relevance for that document. The relevance system may aggregate the query term relevances into a document relevance.

Abstract: A system for learning an attention model for an image based on user navigation actions while viewing the image is provided. An attention model learning system generates an initial attention model based on static features derived from the image. The learning system logs the actions of users as they view the image. The learning system identifies from the actions of the users those areas of the image that may be of user interest: After the learning system identifies areas that may be of user interest, the learning system attempts to identify attention objects based on those identified areas. After identifying the user attention objects, the learning system updates the attention model for the image to reflect the additional information provided by the user attention objects.

Abstract: Systems and methods to present web image search results for effective image browsing are described. In one aspect, task-based attention objects for each of multiple images associated with image search results are generated. Thumbnail images from respective ones of the images are created as a function of at least the task-based attention objects. The thumbnail images emphasize image region(s) of greater priority to a user in view of a keyword or expanded keyword associated with the search results.

Abstract: An importance system calculates the importance of pages using a conditional Markov random walk model rather than a conventional Markov random walk model. The importance system calculates the importance of pages factoring in the importance of sites that contain those pages. The importance system may factor in the importance of sites based on the strength of the correlation of the importance of a page to the importance of a site. The strength of the correlation may be based upon the depth of the page within the site. The importance system may iteratively calculate the importance of the pages using “conditional” transition probabilities. During each iteration, the importance system may recalculate the conditional transition probabilities based on the importance of sites that are derived from the recalculated importance of pages during the iteration.

Abstract: A method and system for determining similarity or correlation between categories of a hierarchical taxonomy for documents by combining heterogeneous similarity metrics is provided. A correlation system uses both a taxonomy distance metric and a term space distance metric to represent the similarity between categories. The correlation system finds a new distance metric for categories that factors in both the taxonomy distance metric and the term space distance metric. The new distance metric can then be used by classifiers to more accurately represent the correlation between categories.

Abstract: A method and system for learning-based assessment of the quality of an image is provided. An image quality assessment system trains an image classifier based on a training set of sample images that have quality ratings. To train the classifier, the assessment system generates a feature vector for each sample image representing various attributes of the image. The assessment system may train the classifier using an adaptive boosting technique to calculate a quality score for an image. Once the classifier is trained, the assessment system may calculate the quality of an image by generating a feature vector for that image and applying the trained classifier to the feature vector to calculate the quality score for the image.

Abstract: By understanding a website author's intention through an analysis of the function of a website, website content can be adapted for presentation or rendering in a manner that more closely appreciates and respects the function behind the website. A website's function is analyzed so that its content can be adapted to different client environments. A function-based object model (FOM) identifies objects associated with a website, and analyzes those objects in terms of their functions. Desktop oriented websites are adapted for mobile devices based on the FOM and on a mobile control intermediary language.

Abstract: A method and system for determining similarity between items is provided. To calculate similarity scores for pairs of items, the similarity system initializes a similarity score for each pair of objects and each pair of features. The similarity system then iteratively calculates the similarity scores for each pair of objects based on the similar scores of the pairs of features calculated during a previous iteration and calculates the similarity scores for each pair of features based on the similarity scores of the pairs of objects calculated during a previous iteration. The similarity system implements an algorithm that is based on a recursive definition of the similarities between objects and between features. The similarity system continues the iterations of recalculating the similarity scores until the similarity scores converge on a solution.

Abstract: A method and system for classifying display pages based on automatically generated summaries of display pages. A web page classification system uses a web page summarization system to generate summaries of web pages. The summary of a web page may include the sentences of the web page that are most closely related to the primary topic of the web page. The summarization system may combine the benefits of multiple summarization techniques to identify the sentences of a web page that represent the primary topic of the web page. Once the summary is generated, the classification system may apply conventional classification techniques to the summary to classify the web page. The classification system may use conventional classification techniques such as a Naïve Bayesian classifier or a support vector machine to identify the classifications of a web page based on the summary generated by the summarization system.

Abstract: A labeling system uses a two-dimensional conditional random fields technique to label the object elements. The labeling system represents transition features and state features that depend on object elements that are adjacent in two dimensions. The labeling system represents the grid as a graph of vertices and edges with a vertex representing an object element and an edge representing a relationship between the object elements. The labeling system represents each diagonal of the graph as a sequence of states. The labeling system selects a labeling for the vertices of the diagonals that has the highest probability based on transition probabilities between vertices of adjacent diagonals and on the state probabilities of a position within a diagonal.

Abstract: A method and system for identifying information about people is provided. The information system identifies groups of people that have relationships based on their relationships to documents or more generally to objects. The information system initially is provided with an indication of which people have which relationships to which documents. The information system then identifies clusters of people based on having a relationship to the same objects. The information system may also identify clusters of related objects associated with a cluster of people. When a user wants to identify information about a person, the user can provide the name of that person to the information system. The information system then can retrieve and display the names of the other people who are in the same cluster as the person.

Abstract: A method and system for cropping an image is provided. The cropping system automatically crops an image by selecting an image template whose condition is best satisfied by the image and then by selecting a cropping of the image that best attains the goal of the selected image template. The cropping system may use a metric or objective function to rate how well a cropping attains the goal of the selected image template. The cropping system may apply various optimization algorithms to identify a cropping that is the best as indicated by the metric. The cropping system can then automatically crop the image based on the identified cropping.

Abstract: A mechanism to classify source documents into one of two categories, either likely to contain desired information or unlikely to contain desired information. Generally some form of rules based classification in conjunction with deeper analysis using advanced techniques on difficult cases is utilized. The rules based classification is generally good for eliminating cases from further consideration and for identifying documents of interest based on generally discernable relationships between data or based on the presence or absence of data. The deeper analysis is used to uncover more complex relationships between data that may identify documents of interest. Portions of the process may use the entire document while other portions of the process may use only a portion of the document.

Abstract: A method and system for prioritizing communications based on classifications of sentences within the communications is provided. A sentence classification system may classify sentences of communications according to various classifications such as “sentence mode.” The sentence classification system trains a sentence classifier using training data and then classifies sentences using the trained sentence classifier. After the sentences of a communication are classified, a document ranking system may generate a rank for the communication based on the classifications of the sentences within the communication. The document ranking system trains a document rank classifier using training data and then calculates the rank of communications using the trained document rank classifier.