Abstract: A search engine for objects in a corpus of document dynamically evaluates search rank of the objects through Natural Language Processing and machine learning. When a search query is received for a first object, the search engine identifies search results including a plurality of source values that are tied to the first object in the corpus of published documents. A search rank is computed for each identified search result based on content of direct textual references to each of the plurality of source values within the corpus of published documents, as well as a weight assigned to each published document. The identified search results are returned according to the computed search rank.

Abstract: A search engine for objects in a corpus of document dynamically evaluates search rank of the objects through Natural Language Processing and machine learning. When a search query is received for a first object, the search engine identifies search results including a plurality of source values that are tied to the first object in the corpus of published documents. A search rank is computed for each identified search result based on content of direct textual references to each of the plurality of source values within the corpus of published documents, as well as a weight assigned to each published document. The identified search results are returned according to the computed search rank.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyses, objects are merged together with the context of search results of a search engine.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyses, objects are merged together with the context of search results of a search engine.

Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyzes, objects are merged together with the context of search results of a search engine.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Disclosed herein are methods, systems, and apparatuses, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining, from a corpus of journals, a plurality of objects. The corpus is analyzed for contextual clues as to the nature of each of these objects. Contextual analysis may include an analysis of particular fields of metadata to do with the objects. Another example of contextual analysis involves identification of an experiment that a group of objects are commonly associated with and merging objects therefrom. A third contextual analysis example makes use of word vectors about each object. Using these contextual analyses, objects are merged together with the context of search results of a search engine.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: Taught is a search engine for science tools which dynamically evaluates search rank of said science tools through Natural Language Processing and machine learning. The search engine accepts into a corpus of public and private materials, which references individual science tools. Each item of the corpus is evaluated both as to how much that given item should be trusted, and what that item says about individual science tools. Each science tool is evaluated based on what the whole corpus of input data contains concerning those science tools, taking into account how valuable the source of the data is in order to render an overall score and search rank. The search engine generates a judgement of each individual science tool, which is dynamically updated as new information becomes available in the corpus of input data.

Abstract: The present invention describes the scheduling requirements if a business to an automatic scheduling system in a way which allows efficient automatic scheduling of appointments for resources of the business. In one embodiment, the scheduling system schedules the resources based not only on total capacity, but based on how many appointments can be initiated at a given time.

Abstract: Each job is defined in terms of the tasks/services required to do the jobs, using resources needed to carry out those tasks/services at different times during a scheduling period. Each available resource needed for each task/service is associated with a job ID and different start times for a job, forming proposals. The proposals are preferably created prior to the time that any appointments are made to do the job. If an appointment time requested by a customer to have the job done is available among the proposals created, the appointment is scheduled using the proposal. As each appointment is scheduled, changed, or canceled, the available proposals for the job are automatically modified to reflect the changes in the time that each resource is available to do the tasks/services required for the job.

Abstract: The method may include creating a first time span where a time span comprises a start time, an end time and an attribute, creating a second time span; wherein the end time of the first time span and the start time of the second time span are set according to an adjustment rule, allowing modification of the start times and end times, if the end time of the first time span has been modified, automatically adjusting the start time of the second time span according to the adjustment rule and if the start time of the second time span has been modified, automatically adjusting the end time of the first time span according to the adjustment rule.

Abstract: The method may include providing at least one primary calendar, providing a plurality of calendar rules, each of the plurality of rules comprising a rank and a rule-scope. The method may also include providing a representation of the primary calendar and the plurality of calendar rules, and allowing expansion of the representation of the plurality of calendar rules.

Abstract: A nonvolatile power management apparatus that controls the use of power within an integrated circuit. The embodiment varies the power applied to a functional circuit within the integrated circuit. At nominal power, the functional circuit operates normally per nominal operational specifications. Under reduced power, the integrated circuit retains all of its internal states, but has its I/O nets isolated from external circuitry. This prevents latch-up of the functional circuit operating from reduced power (low power input voltage) and prevents external circuitry connected to the integrated circuit from being overloaded.