{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T19:16:44Z","timestamp":1768418204669,"version":"3.49.0"},"reference-count":34,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T00:00:00Z","timestamp":1643414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Combinatorial fusion algorithm (CFA) is a machine learning and artificial intelligence (ML\/AI) framework for combining multiple scoring systems using the rank-score characteristic (RSC) function and cognitive diversity (CD). When measuring the relevance of a publication or document with respect to the 17 Sustainable Development Goals (SDGs) of the United Nations, a classification scheme is used. However, this classification process is a challenging task due to the overlapping goals and contextual differences of those diverse SDGs. In this paper, we use CFA to combine a topic model classifier (Model A) and a semantic link classifier (Model B) to improve the precision of the classification process. We characterize and analyze each of the individual models using the RSC function and CD between Models A and B. We evaluate the classification results from combining the models using a score combination and a rank combination, when compared to the results obtained from human experts. In summary, we demonstrate that the combination of Models A and B can improve classification precision only if these individual models perform well and are diverse.<\/jats:p>","DOI":"10.3390\/s22031067","type":"journal-article","created":{"date-parts":[[2022,1,30]],"date-time":"2022-01-30T00:12:56Z","timestamp":1643501576000},"page":"1067","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Improving SDG Classification Precision Using Combinatorial Fusion"],"prefix":"10.3390","volume":"22","author":[{"given":"D. Frank","family":"Hsu","sequence":"first","affiliation":[{"name":"Laboratory of Informatics and Data Mining, Department of Computer and Information Science, Fordham University, New York, NY 10023, USA"}]},{"given":"Marcelo T.","family":"LaFleur","sequence":"additional","affiliation":[{"name":"Department of Economic and Social Affairs, United Nations, New York, NY 10017, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7688-8056","authenticated-orcid":false,"given":"Ilyas","family":"Orazbek","sequence":"additional","affiliation":[{"name":"Laboratory of Informatics and Data Mining, Department of Computer and Information Science, Fordham University, New York, NY 10023, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1608","DOI":"10.1186\/s40064-016-3252-8","article-title":"An Overview of Topic Modeling and Its Current Applications in Bioinformatics","volume":"5","author":"Liu","year":"2016","journal-title":"SpringerPlus"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1145\/2133806.2133826","article-title":"Probabilistic Topic Models","volume":"55","author":"Blei","year":"2012","journal-title":"Commun. 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BMC Genom., 13.","DOI":"10.1186\/1471-2164-13-S8-S12"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1021\/ci050034w","article-title":"Consensus Scoring Criteria for Improving Enrichment in Virtual Screening","volume":"45","author":"Yang","year":"2005","journal-title":"J. Chem. Inf. Modeling"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1504\/IJCBDD.2011.041415","article-title":"LigSeeSVM: Ligand-Based Virtual Screening Using Support Vector Machines and Data Fusion","volume":"4","author":"Chen","year":"2011","journal-title":"Int. J. Comput. Biol. Drug Des."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.inffus.2008.08.009","article-title":"Combining Multiple Scoring Systems for Target Tracking Using Rank\u2013Score Characteristics","volume":"10","author":"Lyons","year":"2009","journal-title":"Inf. Fusion"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"306","DOI":"10.5772\/56344","article-title":"Sensor Feature Selection and Combination for Stress Identification Using Combinatorial Fusion","volume":"10","author":"Deng","year":"2013","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1250008","DOI":"10.1142\/S0219265912500089","article-title":"Combining Multiple Sensor Features for Stress Detection Using Combinatorial Fusion","volume":"13","author":"Deng","year":"2012","journal-title":"J. Interconnect. Netw."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1007\/978-3-030-30143-9_5","article-title":"Improving Portfolio Performance Using Attribute Selection and Combination","volume":"Volume 1080","author":"Esposito","year":"2019","journal-title":"Pervasive Systems, Algorithms and Networks"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s40708-015-0008-0","article-title":"On the Combination of Two Visual Cognition Systems Using Combinatorial Fusion","volume":"2","author":"Batallones","year":"2015","journal-title":"Brain Inform."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2089","DOI":"10.1109\/LCOMM.2017.2709750","article-title":"Vertical Handoff Decision Using Fuzzification and Combinatorial Fusion","volume":"21","author":"Kustiawan","year":"2017","journal-title":"IEEE Commun. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"100415","DOI":"10.1016\/j.patter.2021.100415","article-title":"Ranks Underlie Outcome of Combining Classifiers: Quantitative Roles for Diversity and Accuracy","volume":"3","author":"Sniatynski","year":"2021","journal-title":"Patterns"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1350001","DOI":"10.1142\/S0218213013500012","article-title":"Combination of Multiple Feature Selection Methods for Text Categorization by Using Combinatorial Fusion Analysis And Rank-Score Characteristic","volume":"22","author":"Li","year":"2013","journal-title":"Int. J. Artif. Intell. Tools"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"194001","DOI":"10.1142\/S0219265919400012","article-title":"Cognitive Diversity: A Measurement of Dissimilarity Between Multiple Scoring Systems","volume":"19","author":"Hsu","year":"2019","journal-title":"J. Interconnect. Netw."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3919","DOI":"10.1109\/ACCESS.2020.3047057","article-title":"Multi-Layer Combinatorial Fusion Using Cognitive Diversity","volume":"9","author":"Hurley","year":"2021","journal-title":"IEEE Access"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Rosli, N., Rahman, M., Balakrishnan, M., Komeda, T., Mazlan, S., and Zamzuri, H. (2017). Improved Gender Recognition during Stepping Activity for Rehab Application Using the Combinatorial Fusion Approach of EMG and HRV. Appl. Sci., 7.","DOI":"10.3390\/app7040348"},{"key":"ref_20","unstructured":"(2021, December 22). United Nations The 17 Goals. Available online: https:\/\/sdgs.un.org\/goals."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"LaFleur, M.T. (2019). Art Is Long, Life Is Short: An SDG Classification System for DESA Publications, DESA. Working Paper No. 159.","DOI":"10.2139\/ssrn.3400135"},{"key":"ref_22","unstructured":"LaFleur, M.T., and Kim, N. (2020). What Does the United Nations \u201cSay\u201d about Global Agenda? An Exploration of Trends Using Natural Language Processing for Machine Learning, DESA. Working Paper No. 171."},{"key":"ref_23","unstructured":"Le Blanc, D., Freire, C., and Vierros, M. (2017). Mapping the Linkages between Oceans and Other Sustainable Development Goals: A Preliminary Exploration, DESA. Working Paper No. 149."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Le Blanc, D. (2015). Towards Integration at Last? The Sustainable Development Goals as a Network of Targets, DESA. Working Paper No. 141.","DOI":"10.1002\/sd.1582"},{"key":"ref_25","unstructured":"(2021, December 22). UN DESA LinkedSDGs. Available online: https:\/\/linkedsdg.officialstatistics.org."},{"key":"ref_26","unstructured":"(2021, December 22). W3C Semantic Web. Available online: https:\/\/www.w3.org\/standards\/semanticweb."},{"key":"ref_27","unstructured":"Eastman, M.T., Horrocks, P., Singh, T., and Kumar, N. (2021, December 22). Institutional Investing for the SDGs; MSCI and OECD, 2018. Available online: https:\/\/www.msci.com\/documents\/10199\/239004\/Institutional_Investing_for_the_SDGs.pdf."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"121795","DOI":"10.1016\/j.physa.2019.121795","article-title":"Rank-Frequency Distribution of Natural Languages: A Difference of Probabilities Approach","volume":"532","author":"Cocho","year":"2019","journal-title":"Phys. A Stat. Mech. Appl."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1111\/1467-9787.00129","article-title":"The Return of Zipf: Towards a Further Understanding of the Rank-Size Distribution","volume":"39","author":"Brakman","year":"1999","journal-title":"J. Reg. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Orazbek, I., LaFleur, M.T., and Hsu, D.F. (2021, January 25\u201328). Improving SDG Classification Precision of Topic Models with Combinatorial Fusion Algorithm. Proceedings of the 2021 IEEE Intl Conference on Cyber Science and Technology Congress (CyberSciTech), Calgary, AB, Canada.","DOI":"10.1109\/DASC-PICom-CBDCom-CyberSciTech52372.2021.00091"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1593","DOI":"10.1021\/acs.jcim.0c01307","article-title":"Improving Data and Prediction Quality of High-Throughput Perovskite Synthesis with Model Fusion","volume":"61","author":"Tang","year":"2021","journal-title":"J. Chem. Inf. Modeling"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1007\/s10791-005-6994-4","article-title":"Comparing Rank and Score Combination Methods for Data Fusion in Information Retrieval","volume":"8","author":"Hsu","year":"2005","journal-title":"Inf. Retr."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Debnath, P., Konwar, N., and Radenovi\u0107, S. (2021). Metric Fixed Point Theory: Applications in Science, Engineering and Behavioural Sciences, Springer. Forum for Interdisciplinary Mathematics.","DOI":"10.1007\/978-981-16-4896-0"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Todor\u010devi\u0107, V. (2019). Harmonic Quasiconformal Mappings and Hyperbolic Type Metrics, Springer International Publishing.","DOI":"10.1007\/978-3-030-22591-9"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1067\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:10:47Z","timestamp":1760134247000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/3\/1067"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,29]]},"references-count":34,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["s22031067"],"URL":"https:\/\/doi.org\/10.3390\/s22031067","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,29]]}}}