{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,2]],"date-time":"2022-04-02T22:52:48Z","timestamp":1648939968978},"reference-count":30,"publisher":"World Scientific Pub Co Pte Ltd","issue":"10","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Soft. Eng. Knowl. Eng."],"published-print":{"date-parts":[[2021,10]]},"abstract":" Trigger-action (TA) programming is a programming paradigm that allows end-users to automate and connect IoT devices and online services using if-trigger-then-action rules. Early studies have demonstrated this paradigms usability, but more recent work has also highlighted complexities that arise in realistic scenarios. To facilitate end-users in TA programming, we propose AutoTAR, a context-aware conversational recommendation technique for recommending TA rules. AutoTAR leverages a TA knowledge graph to encode semantic features and abstract functionalities of rules, and then takes a two-phase method to recommend TA rules to end-users: during the context-aware recommendation phase, it elicits user preferences from programming context and recommends the top-N rules using a mixed content and collaborative technique; during the conversational recommendation phase, it justifies recommendations by iteratively raising questions and collecting feedback from end-users. <\/jats:p> We evaluate AutoTAR on Mturk and real data collected from the IFTTT community. The results show that our method outperforms state-of-the-arts significantly\u00a0\u2014 its context-aware recommendation outperforms RecRules by 26% on R@5 and 21% on NDCG@5; its conversational recommendation outperforms LARecommender (a conversational recommender with the LA model) by 67.64% on accuracy. In addition, AutoTAR is effective in solving three problems frequently occurring in TA rule recommendations, i.e., the cold-start problem, the repeat-consumption problem, and the incomplete-intent problem. <\/jats:p>","DOI":"10.1142\/s0218194021500510","type":"journal-article","created":{"date-parts":[[2021,11,15]],"date-time":"2021-11-15T09:58:46Z","timestamp":1636970326000},"page":"1517-1538","source":"Crossref","is-referenced-by-count":0,"title":["Context-Aware Conversational Recommendation of Trigger-Action Rules in IoT Programming"],"prefix":"10.1142","volume":"31","author":[{"given":"Mingxin","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, P.\u00a0R.\u00a0China"}]},{"given":"Qinyue","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, P.\u00a0R.\u00a0China"}]},{"given":"Enze","family":"Ma","sequence":"additional","affiliation":[{"name":"Beijing Forestry University, P.\u00a0R.\u00a0China"}]},{"given":"Beijun","family":"Shen","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, P.\u00a0R.\u00a0China"}]},{"given":"Yuting","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2021,11,15]]},"reference":[{"key":"S0218194021500510BIB002","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-018-9648-9"},{"key":"S0218194021500510BIB007","doi-asserted-by":"publisher","DOI":"10.1145\/2556288.2557420"},{"key":"S0218194021500510BIB008","doi-asserted-by":"publisher","DOI":"10.1145\/3411838"},{"key":"S0218194021500510BIB009","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00051"},{"key":"S0218194021500510BIB010","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91662-0_13"},{"key":"S0218194021500510BIB011","doi-asserted-by":"publisher","DOI":"10.1145\/3344211"},{"key":"S0218194021500510BIB012","doi-asserted-by":"publisher","DOI":"10.1145\/3377325.3377499"},{"key":"S0218194021500510BIB013","first-page":"4574","volume-title":"Advances in Neural Information Processing Systems","author":"Liu C.","year":"2016"},{"key":"S0218194021500510BIB015","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1085"},{"key":"S0218194021500510BIB016","doi-asserted-by":"publisher","DOI":"10.1145\/3399715.3399905"},{"key":"S0218194021500510BIB017","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijhcs.2018.12.008"},{"key":"S0218194021500510BIB018","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300782"},{"key":"S0218194021500510BIB019","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"S0218194021500510BIB020","doi-asserted-by":"publisher","DOI":"10.1109\/IRI49571.2020.00045"},{"key":"S0218194021500510BIB021","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2593720"},{"key":"S0218194021500510BIB022","doi-asserted-by":"publisher","DOI":"10.1561\/1500000016"},{"key":"S0218194021500510BIB023","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.16"},{"key":"S0218194021500510BIB024","doi-asserted-by":"publisher","DOI":"10.1109\/SANER.2019.8668033"},{"key":"S0218194021500510BIB025","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401180"},{"key":"S0218194021500510BIB027","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2883742"},{"key":"S0218194021500510BIB028","volume-title":"Advanced Data Mining Techniques","author":"Olson D. 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