Abstract:
A computer-implemented method and system are provided in which characteristics of a website are analyzed to determine whether the website represents a potential source of spam content. The analysis can include generating a characterizing signature of a webpage containing a content item, and obtaining an occurrence count for the generated characterizing signature. The characterizing signature is derived from formatting data of the webpage. When the obtained occurrence count is greater than a threshold count, the content item can be identified as spam content, and flagged as spam content.
Abstract:
A computer-implemented method is presented herein. The method obtains a first content item from an online source, and then generates a characterizing signature of the first content item. The method continues by finding a previously-saved instance of the characterizing signature and retrieving data associated with a second content item (the second content item is characterized by the characterizing signature). The method continues by analyzing the data associated with the second content item, corresponding data associated with the first content item, and decision criteria. Thereafter, either the first content item or the second content item is identified as an original content item, based on the analyzing. The other content item can be flagged as an aggregated content item.
Abstract:
Disclosed are some implementations of systems, apparatus, methods and computer program products for implementing a scalable computing system. The scalable computing system includes an intermediate system that facilitates communications between a core server system and a third-party system. The core server system processes a client request for a third-party service in association with a web page having a corresponding web address. The intermediate system communicates with the core server system to obtain a session token, and transmits the session token and web address to the third-party system. The third-party system may then access the web page via the web address using the session token.
Abstract:
A database system receives an input for creating a work order and identifies work plan criteria based on the input. The database system uses the work plan criteria to select work plan templates, which includes work steps, from multiple work plan templates. The database system creates a work order, including work plans corresponding to the work plan templates and at least part of the input for creating the work order. The database system displays the work order and receives a selection of an activity object displayed on one of the user interface pages displaying the work steps, and then displays an activity picklist. The database system receives a selection of an activity in the activity picklist, and adds, deletes, or modifies a database record by executing a user action or an automated business process corresponding to the activity in the activity picklist.
Abstract:
Some embodiments of the present invention include a method for processing entities and may include generating, by a computing system, a hierarchical structure representation of entities from a plurality of entities of an object; receiving, by the computing system, information about a current entity; displaying, by the computing system, the current entity and a number of entities related to the current entity using the hierarchical structure representation of the entities, the number of related entities displayed being based on a display range; and updating, by the computing system, the display of the current entity and the related entities based on detecting a scrolling up action on a graphical user interface associated with the computing system.
Abstract:
A system for processing social media data includes a platform with a social media acquisition module configurable to collect a plurality of social media statements. The platform further includes an analysis engine configurable to analyze the plurality of social media statements according to a first sentiment model to generate first analytics data. The analysis engine is configurable to present the first analytics data to a client user, including a display of a sentiment value for each of the social media statements. The platform further includes a feedback queue configurable to receive feedback from the client user on at least a portion of the sentiment values; a model modification module configurable to modify the first sentiment model based on the feedback to result in a modified sentiment model; and a database configurable to store the modified sentiment model as a personalized sentiment model for the client user.
Abstract:
A system for processing social media data includes a platform with a social media acquisition module configurable to collect a plurality of social media statements. The platform further includes an analysis engine configurable to analyze the plurality of social media statements according to a first sentiment model to generate first analytics data. The analysis engine is configurable to present the first analytics data to a client user, including a display of a sentiment value for each of the social media statements. The platform further includes a feedback queue configurable to receive feedback from the client user on at least a portion of the sentiment values; a model modification module configurable to modify the first sentiment model based on the feedback to result in a modified sentiment model; and a database configurable to store the modified sentiment model as a personalized sentiment model for the client user.
Abstract:
A computer-implemented method and system are provided in which characteristics of a website are analyzed to determine whether the website represents a potential source of spam content. The analysis can include generating a characterizing signature of a webpage containing a content item, and obtaining an occurrence count for the generated characterizing signature. The characterizing signature is derived from formatting data of the webpage. When the obtained occurrence count is greater than a threshold count, the content item can be identified as spam content, and flagged as spam content.
Abstract:
A computer-implemented method is presented herein. The method obtains a first content item from an online source, and then generates a characterizing signature of the first content item. The method continues by finding a previously-saved instance of the characterizing signature and retrieving data associated with a second content item (the second content item is characterized by the characterizing signature). The method continues by analyzing the data associated with the second content item, corresponding data associated with the first content item, and decision criteria. Thereafter, either the first content item or the second content item is identified as an original content item, based on the analyzing. The other content item can be flagged as an aggregated content item.
Abstract:
A computer-implemented method is presented herein. The method obtains a first content item from an online source, and then generates a characterizing signature of the first content item. The method continues by finding a previously-saved instance of the characterizing signature and retrieving data associated with a second content item (the second content item is characterized by the characterizing signature). The method continues by analyzing the data associated with the second content item, corresponding data associated with the first content item, and decision criteria. Thereafter, either the first content item or the second content item is identified as an original content item, based on the analyzing. The other content item can be flagged as an aggregated content item.