Abstract: Machine logic that traces increases (or decreases) in query drift by performing the following steps: retrieving a first response list responding to a first query; retrieving a second response list responding to a second query, wherein the second query is based, at least in part, on a topic related to the first query; determining a set of scores for each of the first response list and the second response list, calculating a normalized query commitment (“NQC”) for each of the first response list and the second response list; and responsive to determining that a ratio representing a relative difference between the NQC for the first response list and the NQC for the second response list is above a predetermined threshold, determining to use the second response list to respond to the first query.

Abstract: According to some embodiments of the present invention there is provided a computerized method for labeling a cluster of text documents. The method comprises receiving a document cluster and producing automatically multiple document sub-clusters determined by randomly changing some documents. The method applies multiple cluster labeling algorithms on the cluster and on each sub-cluster, to generate ordered lists. The method comprises generating a ranked label list for each cluster labeling algorithm by computing automatically label values, one for each cluster label in the lists of the selected algorithm, and re-ranking the ordered list. The method combines the re-ranked label lists using a label fusing algorithm to produce a fused label list.

Abstract: A method, including submitting, to a search engine, a first query including, and receiving, in response to the first query, a first list including first results, each of the first results having a respective first ranking. Keywords are derived from the first query, and for each keyword, a respective second query is submitted to the search engine, the respective second query including the first query term and the derived keyword. In response to each of the respective second queries, a respective second list including respective second results is received, each of the respective second results having a second ranking and a corresponding first result, and for each given second result, one or more stability scores are computed based on the second ranking of the given second result and the first ranking of the corresponding first result. The second results are ranked based on their respective one or more stability scores.

Abstract: Machine logic that traces increases (or decreases) in query drift by performing the following steps: retrieving a first response list responding to a first query; retrieving a second response list responding to a second query, wherein the second query is based, at least in part, on a topic related to the first query; determining a set of scores for each of the first response list and the second response list, calculating a normalized query commitment (“NQC”) for each of the first response list and the second response list; and responsive to determining that a ratio representing a relative difference between the NQC for the first response list and the NQC for the second response list is above a predetermined threshold, determining to use the second response list to respond to the first query.

Abstract: A method, including submitting, to a search engine, a first query including, and receiving, in response to the first query, a first list including first results, each of the first results having a respective first ranking. Keywords are derived from the first query, and for each keyword, a respective second query is submitted to the search engine, the respective second query including the first query term and the derived keyword. In response to each of the respective second queries, a respective second list including respective second results is received, each of the respective second results having a second ranking and a corresponding first result, and for each given second result, one or more stability scores are computed based on the second ranking of the given second result and the first ranking of the corresponding first result. The second results are ranked based on their respective one or more stability scores.

Abstract: According to some embodiments of the present invention there is provided a computerized method for labeling a cluster of text documents. The method comprises receiving a document cluster and producing automatically multiple document sub-clusters determined by randomly changing some documents. The method applies multiple cluster labeling algorithms on the cluster and on each sub-cluster, to generate ordered lists. The method comprises generating a ranked label list for each cluster labeling algorithm by computing automatically label values, one for each cluster label in the lists of the selected algorithm, and re-ranking the ordered list. The method combines the re-ranked label lists using a label fusing algorithm to produce a fused label list.