Sequential event prediction
In sequential event prediction, we are given a “sequence database” of past event sequences to learn from, and we aim to predict the next event within a current event sequence. We focus on applications where the set of the past events has predictive power and not the specific order of those past even...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Springer Science+Business Media
2014
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| Online Access: | http://hdl.handle.net/1721.1/88080 |
| _version_ | 1811077595602616320 |
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| author | Letham, Benjamin Rudin, Cynthia Madigan, David |
| author2 | Massachusetts Institute of Technology. Operations Research Center |
| author_facet | Massachusetts Institute of Technology. Operations Research Center Letham, Benjamin Rudin, Cynthia Madigan, David |
| author_sort | Letham, Benjamin |
| collection | MIT |
| description | In sequential event prediction, we are given a “sequence database” of past event sequences to learn from, and we aim to predict the next event within a current event sequence. We focus on applications where the set of the past events has predictive power and not the specific order of those past events. Such applications arise in recommender systems, equipment maintenance, medical informatics, and in other domains. Our formalization of sequential event prediction draws on ideas from supervised ranking. We show how specific choices within this approach lead to different sequential event prediction problems and algorithms. In recommender system applications, the observed sequence of events depends on user choices, which may be influenced by the recommendations, which are themselves tailored to the user’s choices. This leads to sequential event prediction algorithms involving a non-convex optimization problem. We apply our approach to an online grocery store recommender system, email recipient recommendation, and a novel application in the health event prediction domain. |
| first_indexed | 2024-09-23T10:45:31Z |
| format | Article |
| id | mit-1721.1/88080 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T10:45:31Z |
| publishDate | 2014 |
| publisher | Springer Science+Business Media |
| record_format | dspace |
| spelling | mit-1721.1/880802022-09-27T14:44:16Z Sequential event prediction Letham, Benjamin Rudin, Cynthia Madigan, David Massachusetts Institute of Technology. Operations Research Center Sloan School of Management Letham, Benjamin Rudin, Cynthia In sequential event prediction, we are given a “sequence database” of past event sequences to learn from, and we aim to predict the next event within a current event sequence. We focus on applications where the set of the past events has predictive power and not the specific order of those past events. Such applications arise in recommender systems, equipment maintenance, medical informatics, and in other domains. Our formalization of sequential event prediction draws on ideas from supervised ranking. We show how specific choices within this approach lead to different sequential event prediction problems and algorithms. In recommender system applications, the observed sequence of events depends on user choices, which may be influenced by the recommendations, which are themselves tailored to the user’s choices. This leads to sequential event prediction algorithms involving a non-convex optimization problem. We apply our approach to an online grocery store recommender system, email recipient recommendation, and a novel application in the health event prediction domain. 2014-06-23T20:17:15Z 2014-06-23T20:17:15Z 2013-06 2011-11 Article http://purl.org/eprint/type/JournalArticle 0885-6125 1573-0565 http://hdl.handle.net/1721.1/88080 Letham, Benjamin, Cynthia Rudin, and David Madigan. “Sequential Event Prediction.” Mach Learn 93, no. 2–3 (November 2013): 357–380. en_US http://dx.doi.org/10.1007/s10994-013-5356-5 Machine Learning Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Springer Science+Business Media MIT web domain |
| spellingShingle | Letham, Benjamin Rudin, Cynthia Madigan, David Sequential event prediction |
| title | Sequential event prediction |
| title_full | Sequential event prediction |
| title_fullStr | Sequential event prediction |
| title_full_unstemmed | Sequential event prediction |
| title_short | Sequential event prediction |
| title_sort | sequential event prediction |
| url | http://hdl.handle.net/1721.1/88080 |
| work_keys_str_mv | AT lethambenjamin sequentialeventprediction AT rudincynthia sequentialeventprediction AT madigandavid sequentialeventprediction |