Abstract: Aspects of the subject technology include an event processing and prospect identifying platform. It accepts as input a set of storylines (a sequence of entities and their relationships) and processes them as follows: (1) uses different algorithms (LDA, SVM, information gain, rule sets) to identify themes from storylines; (2) identifies top locations and times in storylines and combines with themes to generate events that are meaningful in a specific scenario for categorizing storylines; and (3) extracts top prospects as people and organizations from data elements contained in storylines. The output comprises sets of events in different categories and storylines under them along with top prospects identified. Aspects use in-memory distributed processing that scales to high data volumes and categorizes generated storylines in near real-time.

Abstract: A method and apparatus for recognizing and extracting data from a form depicted within an image of a document are described. The method may include receiving the image of the document, the image depicting the form and data contained one the form. The method may also include transforming the image of the document to a set of one or more key, value pairs by processing the image of the document with a sequence of two or more trained machine learning based image analysis processes, wherein keys are relevant to forms of the type depicted in the form, and wherein each value is associated with a key. The method may also include generating a data output that comprises the set of key, value pairs for textual data recognized and extracted from the form depicted in the image.

Abstract: Aspects of the present disclosure relate to a distributed storytelling framework. A server receives an adjacency list comprising a set of nodes linked together by edges. The server converts the adjacency list to a set of generated storylines, each storyline being represented as a key-value pair. A key represents a first node and a value represents a second node linked to the first node by an edge. The server combines first and second storylines, of the set of generated storylines, to generate an additional storyline in response to a value from a first storyline matching a key from a second storyline. The additional storyline includes a single key and multiple values, and is added to the set of generated storylines. The server repeats combining storylines, of the set of generated storylines, to generate additional storylines. The server provides an output corresponding to at least one of the generated storylines.

Abstract: Drones have become ubiquitous in performing risky and labor intensive areal tasks cheaply and safely. To allow them to be autonomous, their flight plan needs to be pre-built for them. Existing works do not precalculate flight paths but instead focus on navigation through camera based image processing techniques, genetic or geometric algorithms to guide the drone during flight. That makes flight navigation complex and risky. We present automated flight plan builder DIFPL which pre-builds flight plans for drones to survey a large area. The flight plans are built for subregions and fed into drones which allow them to navigate autonomously. DIFPL employs distributed paradigm on Hadoop MapReduce framework. Distribution is achieved by processing sections or subregions in parallel. Experiments performed with network and elevation datasets validate the efficiency of DIFPL in building optimal flight plans.

Abstract: Systems and methods are disclosed for contextual analysis and segmentation of information objects. In accordance with one implementation, information objects, such as web pages and user profiles, may be processed to obtain a list of key terms. An index may be created containing each of the information objects and associated key terms. Information objects may then be matched to contextual segments (i.e., categories of information objects) by submitting terms associated with the contextual segments against the index. Further, thresholding may be applied, so that only the most relevant information objects for a contextual segment are assigned to the contextual segment.

Abstract: Aspects of the subject technology include an event processing and prospect identifying platform. It accepts as input a set of storylines (a sequence of entities and their relationships) and processes them as follows: (1) uses different algorithms (LDA, SVM, information gain, rule sets) to identify themes from storylines; (2) identifies top locations and times in storylines and combines with themes to generate events that are meaningful in a specific scenario for categorizing storylines; and (3) extracts top prospects as people and organizations from data elements contained in storylines. The output comprises sets of events in different categories and storylines under them along with top prospects identified. Aspects use in-memory distributed processing that scales to high data volumes and categorizes generated storylines in near real-time.

Abstract: Drones have become ubiquitous in performing risky and labor intensive areal tasks cheaply and safely. To allow them to be autonomous, their flight plan needs to be pre-built for them. Existing works do not precalculate flight paths but instead focus on navigation through camera based image processing techniques, genetic or geometric algorithms to guide the drone during flight. That makes flight navigation complex and risky. We present automated flight plan builder DIFPL which pre-builds flight plans for drones to survey a large area. The flight plans are built for subregions and fed into drones which allow them to navigate autonomously. DIFPL employs distributed paradigm on Hadoop MapReduce framework. Distribution is achieved by processing sections or subregions in parallel. Experiments performed with network and elevation datasets validate the efficiency of DIFPL in building optimal flight plans.

Abstract: Aspects of the present disclosure relate to a distributed storytelling framework. A server receives an adjacency list comprising a set of nodes linked together by edges. The server converts the adjacency list to a set of generated storylines, each storyline being represented as a key-value pair. A key represents a first node and a value represents a second node linked to the first node by an edge. The server combines first and second storylines, of the set of generated storylines, to generate an additional storyline in response to a value from a first storyline matching a key from a second storyline. The additional storyline includes a single key and multiple values, and is added to the set of generated storylines. The server repeats combining storylines, of the set of generated storylines, to generate additional storylines. The server provides an output corresponding to at least one of the generated storylines.

Abstract: In one aspect, a recommendation system offers item recommendations to users based on one or more items known to be liked by the users. An item may be recommended to a user if a similarity indicator for the item, established by determining how much more likely than expected the user will like the item based on the user liking another item, exceeds a predetermined threshold. Multiple items may be recommended to a user based on relative similarity indicators.

Abstract: Systems and methods are disclosed for contextual analysis and segmentation of information objects. According to one implementation, information objects, such as web pages and user profiles, may be analyzed to identify key terms. These key terms may be included in a contextual representation of an information object. By comparing the contextual representations of a plurality of information objects, one or more contextual segments (i.e., categories of information objects) may be created. Each contextual segment may also be associated with its own contextual representation. Once a contextual segment has been created, information objects may be assigned to the contextual segment. These contextual segments may be used to deliver targeted advertising, for example.

Abstract: A computer-implemented method is provided for managing online user profiles. The method includes receiving information about online activity of a user, the information including at least a unique user ID and a URL requested by the user; fetching textual content associated with the URL requested by the user; generating one or more keywords based on the textual content; and generating or updating a user profile of the user to include the one or more keywords. A system for managing online user profiles is also provided.

Abstract: A recommendation system is disclosed that in one aspect offers item recommendations to users based on one or more items known to be liked by the users. An item may be recommended to a user if a similarity indicator for the item, established by determining how much more likely than expected the user will like the item based on the user liking another item, exceeds a predetermined threshold. Multiple items may be recommended to a user based on relative similarity indicators.

Abstract: Systems and methods are disclosed for contextual analysis and segmentation of information objects. According to one implementation, information objects, such as web pages and user profiles, may be analyzed to identify key terms. These key terms may be included in a contextual representation of an information object. By comparing the contextual representations of a plurality of information objects, one or more contextual segments (i.e., categories of information objects) may be created. Each contextual segment may also be associated with its own contextual representation. Once a contextual segment has been created, information objects may be assigned to the contextual segment. These contextual segments may be used to deliver targeted advertising, for example.

Abstract: Systems and methods are disclosed for contextual analysis and segmentation of information objects. In accordance with one implementation, information objects, such as web pages and user profiles, may be processed to obtain a list of key terms. An index may be created containing each of the information objects and associated key terms. Information objects may then be matched to contextual segments (i.e., categories of information objects) by submitting terms associated with the contextual segments against the index. Further, thresholding may be applied, so that only the most relevant information objects for a contextual segment are assigned to the contextual segment.

Abstract: Techniques for measuring client-side performance include intercepting an item that is to be sent to a client process prior to the arrival of the item at the client process. The item is modified to produce a modified item that includes code. The code causes a processor on the client device to measure performance related to a service associated with the item. The code also causes the processor to perform one or more acts based on a measurement resulting from measuring performance. The modified item is sent to the client process.

Abstract: A planning system and method for dynamically generating an invisible hierarchy during a planning session in an OLAP type tool. The planning system comprises: (1) a loading mechanism for loading a plan segment, wherein the plan segment is a portion of a plan cube and comprises data, rules, and a defined hierarchy within a dimension; (2) a checking mechanism for determining whether any of the rules associated with the plan segment reference data outside of the plan segment; and (3) a mechanism for creating an invisible hierarchy, wherein the invisible hierarchy comprises the defined hierarchy and at least one ancestor of a top member of the defined hierarchy.