Abstract: A computer-implemented method may include: providing an extension for a web browser, the extension having a user interface configured to occupy a portion of a user interface associated with the web browser; intercepting content fetched by the web browser for a web page being a company page, a social media page, or a professional page; processing the fetched content for the web page to extract information including: a company name, a candidate name, a job title, and/or an industry name; querying a database for contextual information based on the extracted information, the contextual information being a summary of information obtained from one or more sources other than the web page; and presenting, via the user interface, the contextual information including: company information based on the company name, candidate information based on the candidate name, job title information based on the job title, and/or industry information based on the industry name.

Abstract: In some embodiments, status scores representing the status of an entity at various times are determined. Classifiers may be used to translate the status scores into status levels, and visual representations of the progression of the entity's status levels over time may be generated. In some embodiments, predictive models are used to detect outlying events and entities based on the status scores. Some predictive models may be used to predict whether an entity is an outlying candidate for a transition from one state to another state. Other predictive models may be used to predict whether an entity is an outlier relative to a group of other entities.

Abstract: Entity resolution techniques and systems are described. An entity resolution method may include estimating a joint probability of occurrence of a plurality of values of a respective plurality of descriptors of an entity. The plurality of descriptor values may be included in a first data set. The method may further include determining that the joint probability of occurrence of the plurality of descriptor values is less than a threshold probability, identifying a second data set including the same plurality of values of the same respective plurality of descriptors, and determining, based at least in part on the joint probability of occurrence of the plurality of descriptor values being less than the threshold probability and on the first and second data sets including the same plurality of descriptor values, that the first and second data sets describe the same entity.