Scalable trend detection in a personalized search context

Patent metadata

Field	Value
Publication number	US-10210214-B2
Application number	US-201414469597-A
Country	US
Kind code	B2
Filing date	Aug 27, 2014
Priority date	Aug 27, 2014
Publication date	Feb 19, 2019
Grant date	Feb 19, 2019

Abstract

A computer implemented method, a computerized system and a computer program product for detecting scalable trends in a personalized search context. The computer implemented method comprising obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp. The method further comprises calculating, by a processor, in response to obtaining the search results, trend scores for the events based on the occurrences comprised by the search results. The method further comprises providing an output to the user based on the trend scores.

First claim

What is claimed is:

1. A computer-implemented method comprising:
obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp;
in response to obtaining the search results, calculating, by a processor, trend scores for the events based on the occurrences comprised by the search results, wherein said calculating comprises recursively calculating the trend scores for the events using a formula recursive in time, whereby a trend score of an event at a specific time is based on the trend score for the event at a previous time, and on a weighted average of an arrival rate of the event at the specific time; and
providing an output to the user based on the trend scores,
wherein computation of the trend score has complexity of O(n) wherein n is a number of the occurrences comprised in the search results, and
wherein said recursive calculating is based on the following recursive formula:
trendScore( t, i )=β·trendScore( t,i− 1)+eventScore−serviceRate( t,i ),

wherein t is an event, wherein i is a time, wherein trendScore(t,i) is a trend score of the event at time i based on the occurrences at and before time i, wherein eventScore is a score of the event at time i based on occurrences of the event at time i, wherein serviceRate is the weighted average of the arrival rate of the event t at time i, and wherein β is a constant.

2. The computer implemented method of claim 1 , wherein a calculation duration of said calculating is less than one minute.

3. The computer-implemented method of claim 1 , wherein said calculating is performed by a single pass on the occurrences comprised by the search results.

4. The computer implemented method of claim 1 further comprises filtering the occurrences of the events based on a timeframe.

5. A computerized apparatus having a processor, the processor being adapted to perform the steps of:
obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp;
in response to obtaining the search results, calculating trend scores for the events based on the occurrences comprised by the search results, wherein said calculating comprises recursively calculating the trend scores for the events using a formula recursive in time, whereby a trend score of an event at a specific time is based on the trend score for the event at a previous time, and on a weighted average of an arrival rate of the event at the specific time; and
providing an output to the user based on the trend scores,
wherein computation of the trend score has complexity of O(n) wherein n is a number of the occurrences comprised in the search results, and
wherein said recursive calculating is based on the following recursive formula:
trendScore( t,i )=β·trendScore( t,i− 1)+eventScore−serviceRate( t,i ),

wherein t is an event, wherein i is a time, wherein trendScore(t,i) is a trend score of the event at time i based on the occurrences at and before time i, wherein eventScore is a score of the event at time i based on occurrences of the event at time i, wherein serviceRate is the weighted average of the arrival rate of the event t at time i, and wherein β is a constant.

6. The computerized apparatus of claim 5 , wherein a calculation during of said calculating is less than one minute.

7. The computerized apparatus of claim 5 , wherein said calculating is performed by a single pass on the occurrences comprised by the search results.

8. A computer program product comprising a computer readable storage medium retaining program instructions, which program instructions when read by a processor, cause the processor to perform a method comprising:
obtaining search results matching a search query, wherein the search query is a query defined by a user, wherein the search results comprise occurrences of events, wherein each occurrence is associated with a timestamp;
in response to obtaining the search results, calculating trend scores for the events based on the occurrences comprised by the search results, wherein said calculating comprises recursively calculating the trend scores for the events using a formula recursive in time, whereby a trend score of an event at a specific time is based on the trend score for the event at a previous time, and on a weighted average of an arrival rate of the event at the specific time; and
providing an output to the user based on the trend scores,
wherein computation of the trend score has complexity of O(n) wherein n is a number of the occurrences comprised in the search results, and
wherein said recursive calculating is based on the following recursive formula:
trendScore( t,i )=β·trendScore( t,i− 1)+eventScore−serviceRate( t,i ),

wherein t is an event, wherein i is a time, wherein trendScore(t,i) is a trend score of the event at time i based on the occurrences at and before time i, wherein eventScore is a score of the event at time i based on occurrences of the event at time i, wherein serviceRate is the weighted average of the arrival rate of the event t at time i, and wherein β is a constant.

Assignees

• IBM

Inventors

• Guy Ido
• Hashavit Anat
• Kutiel Gilad
• Levin Roy
• Steier Tal

Classifications

• G06F17/30864

  Physics · mapped topic

• G06F17/30867

  Physics · mapped topic

• G06F17/30516 Primary

  Physics · mapped topic

• G06F17/3053

  Physics · mapped topic

• G06F17/30554

  Physics · mapped topic