Systems and methods for constructing and using models of memorability in computing and communications applications

• US 20060129606A1
• Filed: 02/06/2006
• Published: 06/15/2006
• Est. Priority Date: 02/04/2003
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Dumais, Susan T., Horvitz, Eric J., Cutrell, Edward B., Koch, Paul B., Ringel, Meredith J.
• Application Number:
  US11/348,018
• Publication Number:
  US 20060129606A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/148 File search processing
• CPC Class Codes: G06F 16/40 of multimedia data, e.g. slideshows comprising image and additional audio data retrieval of still image data G06F16/50; retrieval of audio data G06F16/60; retrieval of video data G06F16/70
• CPC Class Codes: G06F 16/48 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires

Abstract

One or more models of memorability are provided that facilitate various computer-based applications including those centering on the storage, retrieval, and processing of information, applications that remind people about items they risk not recalling or overlooking, and facilitating communications of reminders. In one application, the models are used to help compose and navigate large personal stores of information about a user'"'"'s activities, communications, images, and other content. In another application, views of files in directories are extended with the addition of memory landmarks, and a means for controlling the number of landmarks provided via changing a threshold on inferred memorability. Another application centers on the use of models of memorability to select subsets of images from larger sets representing events, for display in a slide show or ambient photo display. In another application, a system is provided that facilitates computer-based searching for information by providing for the design and analysis of timeline visualizations in connection with displaying results to queries based at least in part on an index of content. A query is received by a query component (which can be part of search engine that provides a unified index of information a user has been exposed to). The query component parses the query into portions relevant to effecting a meaningful search in accordance with the subject invention. The query component can access and populate a data store which may include information searched for. A landmark component receives and/or accesses information from the query component as well as the data store, and anchors public and/or personal landmark events to search results-related information.

Claims

1. A system employing memorability models, comprising:

one or more memorability models that automatically capture an ability of people to recognize events as landmarks in time; and

an application that employs the memorability models to facilitate processing of information in accordance with the events.

4. The system of claim 1, the memorability models are employed to provide a personalized index containing landmarks in time, the index is employed in at least one application relating to browsing directories of information and in reviewing results of a search engine.

5. The system of claim 1, the memorability models can include at least one of voting models, heuristic models, rules models, statistical models, and complimentary models that are based on patterns.

6. The system of claim 5, the voting models automatically poll a set of users in order to score the memorability of public events.

7. The system of claim 6, the score is based on scalar measures of memorability that include at least one of salience of news stories taken from a corpus of news stories and querying a set of people to assign a value.

8. The system of claim 5, the heuristic models utilize properties of messages and create informal policies that assign scores or deterministic categories of memorability based on functions of the properties.

9. The system of claim 8, further comprising a heuristic function that analyzes the increasing duration of events on a calendar as positively influencing the memorability of the events.

10. The system of claim 9, the heuristic function is applied to which images or subsets of images from a set of images serve as the most memorable of sets of images taken at the event based one or more properties of the images.

11. The system of claim 9, the properties include at least one of a composition of objects in a scene, a color histogram, faces recognized, features involving the sequence and temporal relationships among pictures, a picture associated with short inter-picture intervals, a capturing of excitement of a photographer about an aspect of the events, and properties that indicate that a user'"'"'s activity with regard to the image.

2. The system of claim 2, the memorability models include procedures and policies for assigning a measure of memorability to events that can be employed by various computer-based applications to aid users in processing, receiving, and/or communicating information.

3. The system of claim 2, the events can include at least one of appointments, annotations in a user'"'"'s calendar, holidays, news stories over time, and images.

12. A method for applying memorability information, comprising:

automatically labeling events or items with numerical or categorical labels according to a measure of the likelihood that an item will be recalled, recognized as a landmark, or be most representative of an event or time; and

applying the labeling to information-management applications.

13. The method of claim 12, further comprising employing mathematical functions that assign a scalar measure of salience of events or items as being recalled, recognized as landmarks, or most representative of events or times.

14. The method of claim 13, further comprising at least one of:

applying statistical models of memorability via machine learning methods that are trained implicitly or with an explicit training system;

collecting information about a sample of memorable or non-memorable events or items that provides real-time inference or classification about the likelihood that an event or items as being recalled, recognized as landmarks, or be most representative of events or times; and

providing a probability distribution over different degrees of the event or item.

15. The method of claim 12, further comprising automatically filtering a stream of heterogeneous events and content, so as to selectively store events for log of lifetime events.

16. The method of claim 12, further comprising hierarchically browsing a log of heterogeneous events and content or browsing data at different levels of temporal precision.

17. The method of claim 12, further comprising employing representative landmarks and memorability to selectively choose pictures for an ambient display of pictures drawn from a picture library.

18. The method of claim 12, further comprising employing representative memory landmarks and memorability to selectively choose a set of pictures in a slide show over time or at different points in time about one or more events, under constraints in the total number of slides that a user desires to show.

19. The method of claim 12, further comprising employing representative memory landmarks and memorability to selectively choose a set of items to characterize or summarize the contents of a corpus of items.

20. The method of claim 12, the information-management applications are applied to at least one of a memorability application, relating to will an item be recalled and understood, a memorable landmark relating to will an item be viewed as a milestone in time, and a representative landmark relating to is the item representative of a period of time, event, or sequence of events.