Abstract: This disclosure relates to method and system for improving relevancy and ranking of a search result for a search query. The method may include accessing documents of the search result. Each document may be associated with derived document features that may be derived based on an evaluation of document features with respect to query features. For each document, the method may further include determining a feature score for each of the derived document features based on one or more of the query features and initializing each element of an order array with the feature score for each ordered document feature. The ordered document features may be the derived document features that are ordered based on pre-defined rules. The method may further include ranking the documents by comparing and ranking the order array for each of the documents and presenting an updated search result based on the ranking of the documents.

Abstract: This disclosure relates to method and system for improving relevancy and ranking of a search result for a search query. The method may include accessing documents of the search result. Each document may be associated with derived document features that may be derived based on an evaluation of document features with respect to query features. For each document, the method may further include determining a feature score for each of the derived document features based on one or more of the query features and initializing each element of an order array with the feature score for each ordered document feature. The ordered document features may be the derived document features that are ordered based on pre-defined rules. The method may further include ranking the documents by comparing and ranking the order array for each of the documents and presenting an updated search result based on the ranking of the documents.

Abstract: This disclosure relates to method and system for improving relevancy and ranking of a search result from an index-based search for a given search query. The method may include accessing a number of documents of the search result. Each of the documents may be associated with a number of document natural language (NL) feature metadata, a number of document indexing metadata, and at least one document class. The method may further include determining at least one query class, a number of query NL feature metadata, and a number of query indexing metadata for the given search query. The method may further include determining at least one of a relevancy and a ranking of each of the documents using a set of pre-defined rules, and presenting an updated search result based on the at least one of the relevancy and the ranking of each of the documents.

Abstract: Disclosed subject matter relates generally to image processing that includes a method of automatically establishing a relationship between a plurality of User Interface (UI) elements. The present disclosure provides detailed insights related to each UI element in each input image of an application utilizing minimal human intervention. An image processing system identities the UI elements and positions of the UI elements in input images received from one or more sources. Further, a label corresponding to each UI element in each input image is obtained. Finally, a level of each UI element identified in each UI screen is determined to automatically establish the relationship between the UI elements across UI screens. The relationship is established automatically between the plurality of UI elements in real-time, that helps in easy navigation within the UI screen and among the UI screens of the application.