Clustering Partial Lexicographic Preference Trees (Student Abstract). Allen*, J., Liu, X., Reddivari, S., & Umapathy, K. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. AAAI Press (Acceptance rate: <font color="red">49%</font>).
Paper
Paper abstract bibtex 18 downloads In this work, we consider distance-based clustering of partial lexicographic preference trees (PLP-trees), intuitive and compact graphical representations of user preferences over multi-valued attributes. To compute distances between PLP-trees, we propose a polynomial time algorithm that computes Kendall’s τ distance directly from the trees and show its efficacy compared to the brute-force algorithm. To this end, we implement several clustering methods (i.e., spectral clustering, affinity propagation, and agglomerative nesting) augmented by our distance algorithm, experiment with clustering of up to 10,000 PLP-trees, and show the effectiveness of the clustering methods and visualizations of their results.
@inproceedings{conf/aaai21/AllenLRU,
author = {Joseph Allen* and Xudong Liu and Sandeep Reddivari and Karthikeyan Umapathy},
booktitle = {Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI)},
publisher = {AAAI Press (Acceptance rate: <font color="red">49%</font>)},
title = {Clustering Partial Lexicographic Preference Trees (Student Abstract)},
abstract = {In this work, we consider distance-based clustering of partial lexicographic preference trees (PLP-trees), intuitive and compact graphical representations of user preferences over multi-valued attributes. To compute distances between PLP-trees, we propose a polynomial time algorithm that computes Kendall’s τ distance directly from the trees and show its efficacy compared to the brute-force algorithm. To this end, we implement several clustering methods (i.e., spectral clustering, affinity propagation, and agglomerative nesting) augmented by our distance algorithm, experiment with clustering of up to 10,000 PLP-trees, and show the effectiveness of the clustering methods and visualizations of their results.},
url="https://ojs.aaai.org/index.php/AAAI/article/view/17872",
url_Paper = {http://xudongliu.domains.unf.edu/resources/PLPClustering_aaai21.pdf},
year = 2021
}
Downloads: 18
{"_id":"xhoJg359uq6ofg4BB","bibbaseid":"allen-liu-reddivari-umapathy-clusteringpartiallexicographicpreferencetreesstudentabstract-2021","authorIDs":["bCG5A7bbf9ofp42NR"],"author_short":["Allen*, J.","Liu, X.","Reddivari, S.","Umapathy, K."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Joseph"],"propositions":[],"lastnames":["Allen*"],"suffixes":[]},{"firstnames":["Xudong"],"propositions":[],"lastnames":["Liu"],"suffixes":[]},{"firstnames":["Sandeep"],"propositions":[],"lastnames":["Reddivari"],"suffixes":[]},{"firstnames":["Karthikeyan"],"propositions":[],"lastnames":["Umapathy"],"suffixes":[]}],"booktitle":"Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI)","publisher":"AAAI Press (Acceptance rate: <font color=\"red\">49%</font>)","title":"Clustering Partial Lexicographic Preference Trees (Student Abstract)","abstract":"In this work, we consider distance-based clustering of partial lexicographic preference trees (PLP-trees), intuitive and compact graphical representations of user preferences over multi-valued attributes. To compute distances between PLP-trees, we propose a polynomial time algorithm that computes Kendall’s τ distance directly from the trees and show its efficacy compared to the brute-force algorithm. To this end, we implement several clustering methods (i.e., spectral clustering, affinity propagation, and agglomerative nesting) augmented by our distance algorithm, experiment with clustering of up to 10,000 PLP-trees, and show the effectiveness of the clustering methods and visualizations of their results.","url":"https://ojs.aaai.org/index.php/AAAI/article/view/17872","url_paper":"http://xudongliu.domains.unf.edu/resources/PLPClustering_aaai21.pdf","year":"2021","bibtex":"@inproceedings{conf/aaai21/AllenLRU,\n author = {Joseph Allen* and Xudong Liu and Sandeep Reddivari and Karthikeyan Umapathy},\n booktitle = {Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI)},\n publisher = {AAAI Press (Acceptance rate: <font color=\"red\">49%</font>)},\n title = {Clustering Partial Lexicographic Preference Trees (Student Abstract)},\n\tabstract = {In this work, we consider distance-based clustering of partial lexicographic preference trees (PLP-trees), intuitive and compact graphical representations of user preferences over multi-valued attributes. To compute distances between PLP-trees, we propose a polynomial time algorithm that computes Kendall’s τ distance directly from the trees and show its efficacy compared to the brute-force algorithm. To this end, we implement several clustering methods (i.e., spectral clustering, affinity propagation, and agglomerative nesting) augmented by our distance algorithm, experiment with clustering of up to 10,000 PLP-trees, and show the effectiveness of the clustering methods and visualizations of their results.},\n\turl=\"https://ojs.aaai.org/index.php/AAAI/article/view/17872\",\n url_Paper = {http://xudongliu.domains.unf.edu/resources/PLPClustering_aaai21.pdf},\n year = 2021\n}\n\n","author_short":["Allen*, J.","Liu, X.","Reddivari, S.","Umapathy, K."],"key":"conf/aaai21/AllenLRU","id":"conf/aaai21/AllenLRU","bibbaseid":"allen-liu-reddivari-umapathy-clusteringpartiallexicographicpreferencetreesstudentabstract-2021","role":"author","urls":{"Paper":"https://ojs.aaai.org/index.php/AAAI/article/view/17872"," paper":"http://xudongliu.domains.unf.edu/resources/PLPClustering_aaai21.pdf"},"metadata":{"authorlinks":{"liu, x":"https://bibbase.org/show?bib=http%3A%2F%2Fxudongliu.domains.unf.edu%2Fresources%2Fmypubs.bib&commas=true&msg=embed&noBootstrap=1"}},"downloads":18},"bibtype":"inproceedings","biburl":"http://xudongliu.domains.unf.edu/resources/mypubs.bib","creationDate":"2020-12-07T16:39:09.657Z","downloads":18,"keywords":[],"search_terms":["clustering","partial","lexicographic","preference","trees","student","abstract","allen*","liu","reddivari","umapathy"],"title":"Clustering Partial Lexicographic Preference Trees (Student Abstract)","year":2021,"dataSources":["HyNr96TFpCK8GJyjb","ZC4hkxYmM7m8bqanF","nZ4KWueyniryTd5G3"]}