{"product_id":"9783319289212","title":"SpringerBriefs in Computer Science: Role of Power Law Distribution","description":"\u003ch1\u003eSpringerBriefs in Computer Science: Role of Power Law Distribution\u003c\/h1\u003e \u003ch2\u003eVirinchi, Srinivas; Mitra, Pabitra\u003c\/h2\u003e \u003cp\u003e\u003c\/p\u003e\u003cp\u003eThis\nwork presents link prediction similarity measures for social networks that exploit\nthe degree distribution of the networks. In the context of link prediction in\ndense networks, the text proposes similarity measures based on Markov inequality\ndegree thresholding (MIDTs), which only consider nodes whose degree is above a threshold\nfor a possible link. Also presented are similarity measures based on cliques\n(CNC, AAC, RAC), which assign extra weight between nodes sharing a greater number\nof cliques. Additionally, a locally adaptive (LA) similarity measure is\nproposed that assigns different weights to common nodes based on the degree\ndistribution of the local neighborhood and the degree distribution of the\nnetwork. In the context of link prediction in dense networks, the text\nintroduces a novel two-phase framework that adds edges to the sparse graph to\nforma boost graph.\u003cbr\u003e\u003c\/p\u003e \u003ch3\u003eDetails\u003c\/h3\u003e \u003cp\u003ePublished by: Springer\u003c\/p\u003e \u003cp\u003ePublication Date: 2016-01-29\u003c\/p\u003e \u003cp\u003eFormat: Paperback\u003c\/p\u003e \u003cp\u003eISBN-13: 9783319289212\u003c\/p\u003e \u003cp\u003eDOI: 10.1007\/978-3-319-28922-9\u003c\/p\u003e \u003cp\u003eDimensions: 235cm x155cm\u003c\/p\u003e \u003cp\u003ePages: 67\u003c\/p\u003e ","brand":"Springer International Publishing","offers":[{"title":"Default Title","offer_id":45548511854732,"sku":"9783319289212","price":49.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783319289212.jpg?v=1772897693","url":"https:\/\/lateknightbooks.com\/products\/9783319289212","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}