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Eng."],"published-print":{"date-parts":[[2021,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Next-generation enterprise management systems are beginning to be developed based on the Systems of Engagement (SOE) model. We visualize an SOE as a set of entities. Each entity is modeled by a single parent document with <jats:italic>dynamic<\/jats:italic> embedded links (i.e., child documents) that contain multi-modal information about the entity from various networks. Since entities in an SOE are generally queried using keywords, our goal is to <jats:italic>efficiently<\/jats:italic> retrieve the top-<jats:italic>k<\/jats:italic> entities related to a given keyword-based query by considering the relevance scores of both their parent and child documents. Furthermore, we extend the afore-mentioned problem to incorporate the case where the entities are geo-tagged. The main contributions of this work are three-fold. First, it proposes an efficient bitmap-based approach for quickly identifying the candidate set of entities, whose parent documents contain all queried keywords. A variant of this approach is also proposed to reduce memory consumption by exploiting skews in keyword popularity. Second, it proposes the two-tier HI-tree index, which uses both hashing and inverted indexes, for efficient document relevance score lookups. Third, it proposes an R-tree-based approach to extend the afore-mentioned approaches for the case where the entities are geo-tagged. Fourth, it performs comprehensive experiments with both real and synthetic datasets to demonstrate that our proposed schemes are indeed effective in providing good top-<jats:italic>k<\/jats:italic> result recall performance within acceptable query response times.<\/jats:p>","DOI":"10.1007\/s41019-021-00173-1","type":"journal-article","created":{"date-parts":[[2021,10,11]],"date-time":"2021-10-11T12:05:12Z","timestamp":1633953912000},"page":"411-433","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Efficient Indexing of Top-k Entities in Systems of Engagement with Extensions for Geo-tagged Entities"],"prefix":"10.1007","volume":"6","author":[{"given":"Anirban","family":"Mondal","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ayaan","family":"Kakkar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nilesh","family":"Padhariya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mukesh","family":"Mohania","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,11]]},"reference":[{"key":"173_CR1","unstructured":"http:\/\/blogs.hbr.org\/cs\/2011\/10\/movingfromtransactiontoeng.html"},{"key":"173_CR2","unstructured":"http:\/\/www-01.ibm.com\/software\/ebusiness\/jstart\/systemsofengagement\/"},{"key":"173_CR3","unstructured":"http:\/\/www.bersin.com\/blog\/post\/Systems-of-Engagement-vs-Systems-of-Record-About-HR-software2c-design-and-Workday.aspx"},{"key":"173_CR4","doi-asserted-by":"crossref","unstructured":"Mondal A, Padhariya N, Mohania MK (2020) Towards efficient retrieval of top-k entities in systems of engagement. 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