{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T16:39:18Z","timestamp":1781714358108,"version":"3.54.5"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,9,21]],"date-time":"2019-09-21T00:00:00Z","timestamp":1569024000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Social Media, Web Portals and, in general, information systems offer their own Application Programming Interfaces (APIs), used to provide large data sets concerning every aspect of day-by-day life. APIs usually provide data sets as collections of JSON documents. The heterogeneous structure of JSON documents returned by different APIs constitutes a barrier to effectively query and analyze these data sets. The adoption of NoSQL document stores, such as MongoDB, is useful for gathering these data sets, but does not solve the problem of querying the final heterogeneous repository. The aim of this paper is to provide analysts with a tool, named HammerJDB, that allows for blind querying collections of JSON documents within a NoSQL document database. The idea below is that users may know the application domain but it may be that they are not aware of the real structures of the documents stored in the database\u2014the tool for blind querying tries to bridge the gap, by adopting a query rewriting mechanism. This paper is an evolution of a technique for blind querying Open Data portals and of its implementation within the Hammer framework, presented in some previous work. In this paper, we evolve that approach in order to query a NoSQL document database by evolving the Hammer framework into the HammerJDB framework, which is able to work on MongoDB databases. The effectiveness of the new approach is evaluated on a data set (derived from a real-life one), containing job-vacancy ads collected from European job portals.<\/jats:p>","DOI":"10.3390\/info10100291","type":"journal-article","created":{"date-parts":[[2019,9,23]],"date-time":"2019-09-23T03:26:32Z","timestamp":1569209192000},"page":"291","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Blind Queries Applied to JSON Document Stores"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2745-3539","authenticated-orcid":false,"given":"Stefania","family":"Marrara","sequence":"first","affiliation":[{"name":"Department of Management, Information and Production Engineering, University of Bergamo, 24129 Bergamo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauro","family":"Pelucchi","sequence":"additional","affiliation":[{"name":"Tabulaex - A Burning-Glass Company, 20126 Milano, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9228-560X","authenticated-orcid":false,"given":"Giuseppe","family":"Psaila","sequence":"additional","affiliation":[{"name":"Department of Management, Information and Production Engineering, University of Bergamo, 24129 Bergamo, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1007\/s10844-017-0488-x","article-title":"WoLMIS: A labor market intelligence system for classifying web job vacancies","volume":"51","author":"Boselli","year":"2018","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pelucchi, M., Psaila, G., and Toccu, M.P. (2017, January 25\u201327). Building a query engine for a corpus of open data. Proceedings of the WEBIST 2017, 13th International Conference on Web Information Systems and Technologies, Porto, Portugal.","DOI":"10.5220\/0006308801260136"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pelucchi, M., Psaila, G., and Toccu, M. (2017, January 25\u201327). Enhanced Querying of Open Data Portals. Proceedings of the International Conference on Web Information Systems and Technologies, Porto, Portugal.","DOI":"10.1007\/978-3-319-93527-0_9"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0165-0114(78)90029-5","article-title":"Fuzzy sets as a basis for a theory of possibility","volume":"1","author":"Zadeh","year":"1978","journal-title":"Fuzzy Sets Syst."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Damiani, E., and Tanca, L. (2000, January 4\u20138). Blind Queries to XML Data. Proceedings of the 11th International Conference on Database and Expert Systems Applications, DEXA 2000, London, UK.","DOI":"10.1007\/3-540-44469-6_32"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Damiani, E., Lavarini, N., Marrara, S., Oliboni, B., Pasini, D., Tanca, L., and Viviani, G. (2002, January 25\u201327). The APPROXML Tool Demonstration. Proceedings of the Advances in Database Technology\u2014EDBT 2002, 8th International Conference on Extending Database Technology, Prague, Czech Republic.","DOI":"10.1007\/3-540-45876-X_52"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1007\/s10844-008-0066-3","article-title":"A fuzzy extension of the XPath query language","volume":"33","author":"Campi","year":"2009","journal-title":"J. Intell. Inf. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/18756891.2016.1180822","article-title":"Fuzzy Approaches to Flexible Querying in XML Retrieval","volume":"9","author":"Marrara","year":"2016","journal-title":"Int. J. Comput. Intell. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Liu, L., and \u00d6zsu, M.T. (2009). Web Data Extraction System. Encyclopedia of Database Systems, Springer.","DOI":"10.1007\/978-0-387-39940-9"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.knosys.2014.07.007","article-title":"Web data extraction, applications and techniques: A survey","volume":"70","author":"Ferrara","year":"2014","journal-title":"Knowl. Based Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1698","DOI":"10.1016\/j.ipm.2019.05.009","article-title":"Query expansion techniques for information retrieval: A survey","volume":"56","author":"Azad","year":"2019","journal-title":"Inf. Process. Manag."},{"key":"ref_12","unstructured":"Lee, H.M., Lin, S.K., and Huang, C.W. (2001, January 2\u20135). Interactive query expansion based on fuzzy association thesaurus for web information retrieval. Proceedings of the 10th IEEE International Conference on Fuzzy Systems, Melbourne, Australia."},{"key":"ref_13","unstructured":"Theobald, M., Weikum, G., and Schenkel, R. (September, January 31). Top-k query evaluation with probabilistic guarantees. Proceedings of the Thirtieth International Conference on Very Large Data Bases-Volume 30, VLDB Endowment, Toronto, ON, Canada."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Cui, H., Wen, J.R., Nie, J.Y., and Ma, W.Y. (2002, January 7\u201311). Probabilistic query expansion using query logs. Proceedings of the 11th International Conference on World Wide Web, Honolulu, HI, USA.","DOI":"10.1145\/511446.511489"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chum, O., Mikulik, A., Perdoch, M., and Matas, J. (2011, January 20\u201325). Total recall II: Query expansion revisited. Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, USA.","DOI":"10.1109\/CVPR.2011.5995601"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chum, O., Philbin, J., Sivic, J., Isard, M., and Zisserman, A. (2007, January 14\u201321). Total recall: Automatic query expansion with a generative feature model for object retrieval. Proceedings of the 2007 IEEE 11th International Conference on Computer Vision, Rio de Janeiro, Brazil.","DOI":"10.1109\/ICCV.2007.4408891"},{"key":"ref_17","unstructured":"Liu, J., Dong, X., and Halevy, A.Y. (2006). Answering Structured Queries on Unstructured Data, Citeseer. WebDB 2006."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kononenko, O., Baysal, O., Holmes, R., and Godfrey, M. (2014). Mining Modern Repositories with Elasticsearch, MSR.","DOI":"10.1145\/2597073.2597091"},{"key":"ref_19","unstructured":"Bia\u0142ecki, A., Muir, R., Ingersoll, G., and Imagination, L. (2012, January 16). Apache Lucene 4. Proceedings of the SIGIR 2012 Workshop on Open Source Information Retrieval, Portland, OR, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Nagi, K. (2015, January 12\u201314). Bringing search engines to the cloud using open source components. Proceedings of the 2015 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K), Lisbon, Portugal.","DOI":"10.5220\/0005632701160126"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Pelucchi, M., Psaila, G., and Maurizio, T. (2017, January 24\u201326). The challenge of using map-reduce to query open data. Proceedings of the 6th International Conference on Data Science, Technology and Applications (DATA 2017), Madrid, Spain.","DOI":"10.5220\/0006487803310342"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1145\/1629175.1629198","article-title":"MapReduce: A flexible data processing tool","volume":"53","author":"Dean","year":"2010","journal-title":"Commun. ACM"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Vavilapalli, V.K., Murthy, A.C., Douglas, C., Agarwal, S., Konar, M., Evans, R., Graves, T., Lowe, J., Shah, H., and Seth, S. (2013, January 1\u20133). Apache hadoop yarn: Yet another resource negotiator. Proceedings of the 4th Annual Symposium on Cloud Computing, Santa Clara, CA, USA.","DOI":"10.1145\/2523616.2523633"},{"key":"ref_24","first-page":"95","article-title":"Spark: Cluster computing with working sets","volume":"10","author":"Zaharia","year":"2010","journal-title":"HotCloud"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Pelucchi, M., Psaila, G., and Toccu, M. (2018). Hadoop vs. Spark: Impact on Performance of the Hammer Query Engine for Open Data Corpora. Algorithms, 11.","DOI":"10.3390\/a11120209"},{"key":"ref_26","first-page":"40","article-title":"A survey on NoSQL stores","volume":"51","author":"Davoudian","year":"2018","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"ref_27","unstructured":"Bray, T. (2019, March 15). The Javascript Object Notation (Json) Data Interchange Format. Available online: https:\/\/buildbot.tools.ietf.org\/html\/rfc7158."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Bordogna, G., Capelli, S., and Psaila, G. (2017, January 2\u20134). A big geo data query framework to correlate open data with social network geotagged posts. Proceedings of the The Annual International Conference on Geographic Information Science, Buffalo, NY, USA.","DOI":"10.1007\/978-3-319-56759-4_11"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bordogna, G., Ciriello, D.E., and Psaila, G. (2017, January 23\u201326). A flexible framework to cross-analyze heterogeneous multi-source geo-referenced information: The J-CO-QL proposal and its implementation. Proceedings of the International Conference on Web Intelligence, Leipzig, Germany.","DOI":"10.1145\/3106426.3106537"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1080\/10095020.2017.1374703","article-title":"A cross-analysis framework for multi-source volunteered, crowdsourced, and authoritative geographic information: The case study of volunteered personal traces analysis against transport network data","volume":"21","author":"Bordogna","year":"2018","journal-title":"Geo-Spat. Inf. Sci."},{"key":"ref_31","unstructured":"Psaila, G., and Fosci, P. (2018, January 21\u201323). Toward an Analist-Oriented Polystore Framework for Processing JSON Geo-Data. Proceedings of the IADIS International Conference Applied Computing, Budapest, Hungaria."},{"key":"ref_32","unstructured":"Winkler, W.E. (1990). String Comparator Metrics and Enhanced Decision Rules in the Fellegi-Sunter Model of Record Linkage. Proceedings of the Section on Survey Research Methods, American Statistical Association."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1145\/219717.219748","article-title":"WordNet: A lexical database for English","volume":"38","author":"Miller","year":"1995","journal-title":"Commun. ACM"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Manning, C.D., Raghavan, P., and Sch\u00fctze, H. (2008). Introduction to Information Retrieval, Cambridge University Press.","DOI":"10.1017\/CBO9780511809071"},{"key":"ref_35","unstructured":"(2018). Tabulaex, Tabulaex."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Amato, F., Boselli, R., Cesarini, M., Mercorio, F., Mezzanzanica, M., Moscato, V., Persia, F., and Picariello, A. (2015, January 7\u20139). Challenge: Processing web texts for classifying job offers. Proceedings of the 2015 IEEE International Conference on Semantic Computing (ICSC), Anaheim, CA, USA.","DOI":"10.1109\/ICOSC.2015.7050852"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Shahi, D. (2015). Apache Solr: An Introduction. Apache Solr, Springer.","DOI":"10.1007\/978-1-4842-1070-3"},{"key":"ref_38","unstructured":"Butler, H., Daly, M., Doyle, A., Gillies, S., Schaub, T., and Schmidt, C. (2019, March 15). Geojson Specification. Available online: https:\/\/tools.ietf.org\/html\/rfc7946."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1162\/tacl_a_00051","article-title":"Enriching Word Vectors with Subword Information","volume":"5","author":"Bojanowski","year":"2017","journal-title":"Trans. Assoc. Comput. Linguist."},{"key":"ref_40","unstructured":"Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013). Efficient estimation of word representations in vector space. arXiv."},{"key":"ref_41","unstructured":"Devlin, J., Chang, M.W., Lee, K., and Toutanova, K. (2018). Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/10\/291\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:22:47Z","timestamp":1760188967000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/10\/10\/291"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,21]]},"references-count":41,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,10]]}},"alternative-id":["info10100291"],"URL":"https:\/\/doi.org\/10.3390\/info10100291","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,21]]}}}