A system and method for filtering search results to exclude technically incompatible devices with a user's existing IoT network includes analyzing the search query to determine an objective of a user, calculating a relevance score for each IoT device, profiling an existing IoT network associated with the user, determining a compatibility of each IoT device with the existing IoT network, combining the relevance score and an ease of incorporation score to determine a total score, and filtering the search results for the IoT devices according to the total score, such that an optimal device is displayed at a top of the search results from the search engine on a webpage among other IoT devices that are above a minimum ease of incorporation score and removing other IoT devices from the search results displayed on the webpage that are below the minimum ease of incorporation score.

Search engine filter based on user IoT network

In an example, data in a non-flat format and metadata corresponding to the data are obtained from a first database. The data is flattened into flat data and augmented with the metadata. One or more pieces of the flat data are scanned to locate a first piece of flat data having a first attribute with attribute values that are a subset of attribute values of a second attribute of a second piece of flat data. A link is then created between the first attribute of the first piece of flat data and the second attribute of the second piece of flat data. A graph structure is generated, the graph structure containing a plurality of nodes, each node corresponding to a data type of the flat data and corresponding to one or more pieces of data in the flat data of the corresponding data type.

Internet of things search and discovery graph engine construction

Systems and methods are presented herein for recording portions of a media asset relevant to recording criteria. A media application receives input indicating the recording criteria and identifying a first keyword. The media application accesses a data structure to identify a first node associated with the first keyword. The data structure includes the first node and a plurality of nodes connected to the first node via a plurality of paths. The media application receiving audio component data for a portion of the media asset extracts a term from the audio component data, and identifies a second node in the data structure that is associated with the extracted term. The media application calculates a path score for the portion of the media asset based on a path size in the data structure between the first node and the second node. When the score is high enough, the portion of the media asset is recorded.

Systems and methods for recording relevant portions of a media asset

In an example, a graph structure and flat data corresponding to the graph structure are obtained, the graph structure containing a plurality of nodes Stop words are removed from one or more search terms to obtain modified search terms For each of the modified search terms, the pieces of data from the flat data are searched to locate one or more matching pieces of data from the flat data, wherein a piece of data from the flat data matches if it contains at least one attribute with a value that is similar to the modified search term This information is used to calculate fuzzy match scores for each matching piece of data from the flat data

Internet of things search and discovery using graph engine

In an example, for each one or more search terms, pieces of data from flat data are searched to locate one or more matching pieces of data from the flat data, wherein a piece of data from the flat data matches if it contains at least one attribute with a value that is similar to the search term. Then, for each matching piece of data from the flat data, a fuzzy match score and a match frequency score are calculated. For each node in a graph structure, a ranking score based on a combination of the fuzzy match score and the match frequency score for a corresponding piece of data from the flat data is calculated. One or more search results are retrurned based on the ranking scores of nodes corresponding to pieces of data for the one or more search results.

Internet of things search and discovery dynamic alteration of results

In an example, one or more tokens in a freeform search query are identified, each token corresponding to a search term or combination of neighboring search terms in the freeform search query. A graph structure and flat data corresponding to the graph structure are obtained. A search for results relevant to the identified one or more tokens is performed using a first search process, the first search process using the graph structure and flat data to rank search results according to a first ranking order and populate a why found table. Pieces of data corresponding to the results relevant to the identified one or more tokens are joined using the why found table, forming a view and one or more patterns of operators and terms, in a pattern database, matching the one or more operators and one or more surrounding terms in the freeform search query are found.

Khaitan Priyanka

Papers

Internet of things search and discovery dynamic alteration of results

Internet of things structured query language query formation

Internet of things search and discovery using graph engine