Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example systems and methods related to chatbot skills are described. In one implementation, a system initiates a session to create a new chatbot. The system receives a selection of a first chatbot skill associated with the new chatbot and a selection of a second chatbot skill associated with the new chatbot, where the first chatbot skill is different from the second chatbot skill. The system creates the new chatbot by importing the first chatbot skill and the second chatbot skill into the new chatbot.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: Example systems and methods related to chatbot skills are described. In one implementation, a system initiates a session to create a new chatbot. The system receives a selection of a first chatbot skill associated with the new chatbot and a selection of a second chatbot skill associated with the new chatbot, where the first chatbot skill is different from the second chatbot skill. The system creates the new chatbot by importing the first chatbot skill and the second chatbot skill into the new chatbot.

Abstract: Example natural language processing systems and methods are described. In one implementation, a system receives a request from a remote system, where the request includes text data or voice data. The system analyzes the text data or voice data to determine an intent associated with the request. Based on the intent associated with the request, the system generates a response to the request and communicates the response to the remote system.

Abstract: Disclose are methods for evaluating a user's interests and making gift recommendations using social media data. Interests and attributes of a user may be detected from social media content and products corresponding to the interests and attributes may be selected and presented as gift recommendations for the user. Methods are disclosed for resolving ambiguity as to interests reflected by textual data in social media content. Also disclosed are methods for inferring a user's interests from the interests of friends of the user.

Abstract: A computer implemented method of generating keyword recommendations is provided, which includes providing keyword frequency data in computer readable media that indicate frequency counts of keywords used in past internet searches; providing keyword affinity data in computer readable media that indicate affinities between pairs of keywords used in past user internet searches; identifying keywords from the keyword frequency data that include the selected keyword; identifying keywords from the keyword affinity data that have an affinity to the selected keyword; and prioritizing the identified keywords based upon the keyword frequency.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters. Some or all of the presentations or references are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. The results of such processes might be stored in a presentation details database. A presentation server handles retrieving presentations from the presentation details database for presentation to users along with requests such as search results. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters. Some or all of the presentations or references are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. A presentation server handles retrieving presentations from a presentation details database for presentation to users along with requests such as search results. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters. Some or all of the presentations or references are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. The results of such processes might be stored in a presentation details database. A presentation server handles retrieving presentations from the presentation details database for presentation to users along with requests such as search results. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters, some or all of which are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. The results of such processes might be stored in a presentation details database and a presentation server handles retrieving presentations from there for presentation to users along with requests. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.

Abstract: A presentation system accepts presentations or references to presentations from prospective presenters. Some or all of the presentations or references are stored in a database and referenced by keywords such that presentations to be presented in response to particular searches can be identified. A presentation manager handles accepting bids and settling terms between prospective presenters. The results of such processes might be stored in a presentation details database. A presentation server handles retrieving presentations from the presentation details database for presentation to users along with requests such as search results. Both the presentation manager and the presentation server can operate on a keywords-basis, wherein presentation terms specify keywords to be associated with particular presentations and the presentation server serves particular presentations based on keywords in a search query for which the presentations are to be returned.