{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,15]],"date-time":"2024-09-15T23:49:43Z","timestamp":1726444183251},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2008,8]]},"abstract":"<jats:p>This work addresses a novel problem of maintaining channel proflies on the Web. Such channel maintenance is essential for next generation of Web 2.0 applications that provide sophisticated search and discovery services over Web information channels. Maintaining a fresh channel profile is extremely difficult due to the the dynamic nature of the channel, especially under the constraint of a limited monitoring budget.<\/jats:p>\n          <jats:p>We propose a novel monitoring scheme that learns the channels' monitoring rates. The monitoring scheme is further extended to consider the content that is published on the channels. We describe a novelty detection filter that refines the monitoring rate according to the expected rate of novel content published on the channels. We further show how inter-channel profile similarities can be utilized to refine the channel monitoring rates.<\/jats:p>\n          <jats:p>Using real-world data of Web feeds we study the performance of the monitoring scheme. We experiment with several monitoring policies over a large set of Web feeds and show that a policy based on learning the monitoring rate of the channels, combined with novelty detection, outperforms alternative channel monitoring policies. Our results show that the suggested content-based policy is able to maintain high quality channel profiles under limited monitoring resources.<\/jats:p>","DOI":"10.14778\/1453856.1453878","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"151-162","source":"Crossref","is-referenced-by-count":11,"title":["Maintaining dynamic channel profiles on the web"],"prefix":"10.14778","volume":"1","author":[{"given":"Haggai","family":"Roitman","sequence":"first","affiliation":[{"name":"IBM Haifa Research Lab, Haifa, Israel"}]},{"given":"David","family":"Carmel","sequence":"additional","affiliation":[{"name":"IBM Haifa Research Lab, Haifa, Israel"}]},{"given":"Elad","family":"Yom-Tov","sequence":"additional","affiliation":[{"name":"IBM Haifa Research Lab, Haifa, Israel"}]}],"member":"320","published-online":{"date-parts":[[2008,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/860435.860495"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247620"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/1138394.1138399"},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the 15th Text REtrieval Conference (TREC2006)","author":"Carmel D.","year":"2006","unstructured":"D. Carmel and E. Amitay . Jura at TREC 2006: TAAT versus DAAT in the terabyte track . In Proceedings of the 15th Text REtrieval Conference (TREC2006) . National Institute of Standards and Technology. NIST , 2006 . D. Carmel and E. Amitay. Jura at TREC 2006: TAAT versus DAAT in the terabyte track. In Proceedings of the 15th Text REtrieval Conference (TREC2006). National Institute of Standards and Technology. 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Journal of Artificial Intelligence Research (JAIR), cs.AI\/9605103 , 1996 . L. P. Kaelbling, M. L. Littman, and A. W. Moore. Reinforcement learning: A survey. Journal of Artificial Intelligence Research (JAIR), cs.AI\/9605103, 1996."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.5555\/956418.956595"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/1251086.1251089"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247480.1247536"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/988672.988674"},{"key":"e_1_2_1_18_1","first-page":"360","volume-title":"Proceedings of the 30th International Conference on Very Large Data Bases (VLDB)","author":"Pandey S.","year":"2004","unstructured":"S. Pandey , K. Dhamdhere , and C. Olston . WIC: A general-purpose algorithm for monitoring web information sources . In Proceedings of the 30th International Conference on Very Large Data Bases (VLDB) , pages 360 -- 371 , 2004 . S. Pandey, K. Dhamdhere, and C. Olston. WIC: A general-purpose algorithm for monitoring web information sources. In Proceedings of the 30th International Conference on Very Large Data Bases (VLDB), pages 360--371, 2004."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1060745.1060805"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1281192.1281253"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/1089107.1089111"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/11915072_47"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497593"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497591"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2007.1041"},{"key":"e_1_2_1_27_1","volume-title":"Proceedings of the International Conference on Weblogs and Social Media","author":"Sia K. C.","year":"2007","unstructured":"K. C. Sia , J. Cho , K. Hino , Y. Chi , S. Zhu , and B. L. Tseng . Monitoring rss feeds based on user browsing pattern search . In Proceedings of the International Conference on Weblogs and Social Media , 2007 . K. C. Sia, J. Cho, K. Hino, Y. Chi, S. Zhu, and B. L. Tseng. Monitoring rss feeds based on user browsing pattern search. In Proceedings of the International Conference on Weblogs and Social Media, 2007."},{"key":"e_1_2_1_28_1","first-page":"787","volume-title":"VLDB '06: Proceedings of the 32nd international conference on Very large data bases","author":"Tu Y.-C.","year":"2006","unstructured":"Y.-C. Tu , S. Liu , S. Prabhakar , and B. Yao . Load shedding in stream databases: a control-based approach . In VLDB '06: Proceedings of the 32nd international conference on Very large data bases , pages 787 -- 798 . VLDB Endowment , 2006 . Y.-C. Tu, S. Liu, S. Prabhakar, and B. Yao. Load shedding in stream databases: a control-based approach. 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