Abstract: There are discloses methods and systems for generating a search engine results page (SERP). The method is executable at a server executing a search engine, the server being accessible via a communication network by at least one electronic device. The method comprises, as part of generating a search result list, the search result list containing a first search result and a second search result, predicting a first interest parameter for the first search result; predicting a second interest parameter for the second search result; predicting a usefulness parameter for the first search result, the predicting being at least partially based on the first interest parameter and the second interest parameter; adjusting a position of the first search result within the ranked search result list based on the predicted usefulness parameter, the adjusting resulting in the first search result being at an adjusted position within the ranked search result list.

Abstract: There is disclosed a computer implemented method for training a search ranker, the search ranker being configured to ranking search results. The method comprises: retrieving, by the server, a training dataset including a plurality of training objects; for each training object, based on the corresponding associated object feature vector: determining a weight parameter, the weight parameter being indicative of a quality of the label; determining a relevance parameter, the relevance parameter being indicative of a moderated value of the labels relative to other labels within the training dataset; training the search ranker using the plurality of training objects of the training dataset, the determined relevance parameter for each training object of the plurality of training objects of the training dataset, and the determined weight parameter for each object of the plurality of training objects of the training dataset to rank a new document.

Abstract: There are discloses methods and systems for generating a search engine results page (SERP). The method is executable at a server executing a search engine, the server being accessible via a communication network by at least one electronic device. The method comprises, as part of generating a search result list, the search result list containing a first search result and a second search result, predicting a first interest parameter for the first search result; predicting a second interest parameter for the second search result; predicting a usefulness parameter for the first search result, the predicting being at least partially based on the first interest parameter and the second interest parameter; adjusting a position of the first search result within the ranked search result list based on the predicted usefulness parameter, the adjusting resulting in the first search result being at an adjusted position within the ranked search result list.

Abstract: A computerized method for optimizing search result rankings obtained from a search result ranker has the steps of retrieving a first set of query-document pairs, each query-document pair of the first set having an associated post-impression features vector; generating a weight vector having a number of weights corresponding to a number of post-impression features in each of the post-impression feature vector of the first set; generating a target function by using the weight vector and the post-impression features vectors of the first set; using a performance metric associated with the target function, optimizing the weights of the weight vector using the first set of query-document pairs to obtain an optimized target function; optimizing the search result ranker using the optimized target function; and using the optimized search result ranker to rank search results.

Abstract: A computerized method for optimizing search result rankings obtained from a search result ranker has the steps of retrieving a first set of query-document pairs, each query-document pair of the first set having an associated post-impression features vector; generating a weight vector having a number of weights corresponding to a number of post-impression features in each of the post-impression feature vector of the first set; generating a target function by using the weight vector and the post-impression features vectors of the first set; using a performance metric associated with the target function, optimizing the weights of the weight vector using the first set of query-document pairs to obtain an optimized target function; optimizing the search result ranker using the optimized target function; and using the optimized search result ranker to rank search results.

Abstract: Disclosed are systems, methods and computer program products for classification and segmentation of user's browsing logs based on search goals of the user. In one aspect, the method includes receiving a browsing log of a user; extracting web page features from the browsing log; generating web page classifiers based on the extracted features of the browsing log, wherein different classifiers are related to different search goals of the user; segmenting the browsing log using the one or more classifiers into a plurality of separate logical browsing sessions related to different search goals of the user; and performing an Internet search based on a search query of the user and information about one of the logical browsing sessions.