Using Kindle : your guide to all things Kindle and Kindle DX / by Cheshire, Jim

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Practical recommender systems / by Falk, Kim

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Using Kindle : a complete guide to Amazon's revolutionary wireless reading device / by Cheshire, Jim

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Recommender systems with machine learning.

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Recommender system with machine learning and artificial intelligence : practical tools and applications in medical, agricultural and other industries /

Table of Contents: “…Sujithra Kanmani and B. Surendiran -- Netflix challenge : improving movie recommendations / Vasu Goel -- Product or item-based recommender system / Jyoti Rani, Usha Mittal and Geetika Gupta -- A trust-based recommender system built on IoT blockchain network with cognitive framework / S. …”
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An introduction to search engines and web navigation / by Levene, M. 1957-

Table of Contents: “…-- 9-1-1: Milgram's small-world experiment -- 9-1-2: Collaboration graphs -- 9-1-3: Instant messaging social network -- 9-1-4: Social Web -- 9-1-5: Social network start-ups -- 9-2: Social network analysis -- 9-2-1: Social network terminology -- 9-2-2: Strength of weak ties -- 9-2-3: Centrality -- 9-2-4: Web communities -- 9-2-5: Pajek: Large network analysis software -- 9-3: Peer-to-peer networks -- 9-3-1: Centralized P2P networks -- 9-3-2: Decentralized P2P networks -- 9-3-3: Hybrid P2P networks -- 9-3-4: Distributed hash tables -- 9-3-5: BitTorrent file distribution -- 9-3-6: JXTA P2P search -- 9-3-7: Incentives in P2P systems -- 9-4: Collaborative filtering -- 9-4-1: Amazon_com -- 9-4-2: Collaborative filtering explained -- 9-4-3: User-based collaborative filtering -- 9-4-4: Item-based collaborative filtering -- 9-4-5: Model-based collaborative filtering -- 9-4-6: Content-based recommendation systems -- 9-4-7: Evaluation of collaborative filtering systems -- 9-4-8: Scalability of collaborative filtering systems -- 9-4-9: Case study of Amazon_co_uk -- 9-4-10: Netflix prize -- 9-4-11: Some other collaborative filtering systems -- 9-5: Weblogs (blogs) -- 9-5-1: Blogrolling -- 9-5-2: Blogspace -- 9-5-3: Blogs for testing machine learning algorithms -- 9-5-4: Spreading ideas via blogs -- 9-5-5: Real-time Web and microblogging -- 9-6: Power-law distributions in the Web -- 9-6-1: Detecting power-law distributions -- 9-6-2: Power-law distributions in the Internet -- 9-6-3: Law of surfing and a law of participation -- 9-6-4: Evolution of the Web via preferential attachment -- 9-6-5: Evolution of the Web as a multiplicative process -- 9-6-6: Evolution of the Web via HOT -- 9-6-7: Small-world networks -- 9-6-8: Robustness and vulnerability of a scale-free network -- 9-7: Searching in social networks -- 9-7-1: Social navigation -- 9-7-2: Social search engines -- 9-7-3: Navigation within social networks -- 9-7-4: Navigation within small-world networks -- 9-7-5: Testing navigation strategies in social networks -- 9-8: Social tagging and bookmarking -- 9-8-1: Flickr-sharing your photos -- 9-8-2: YouTube-broadcast yourself -- 9-8-3: Delicious for social bookmarking -- 9-8-4: Communities within content sharing sites -- 9-8-5: Sharing scholarly references -- 9-8-6: Folksonomy -- 9-8-7: Tag clouds -- 9-8-8: Tag search and browsing -- 9-8-9: Efficiency of tagging -- 9-8-10: Clustering and classifying tags -- 9-9: Opinion mining -- 9-9-1: Feature-based opinion mining -- 9-9-2: Sentiment classification -- 9-9-3: Comparative sentence and relation extraction -- 9-10: Web 2_0 and collective intelligence -- 9-10-1: Ajax -- 9-10-2: Syndication -- 9-10-3: Open APIs, mashups, and widgets -- 9-10-4: Software as a service -- 9-10-5: Collective intelligence -- 9-10-6: Algorithms for collective intelligence -- 9-10-7: Wikipedia-the world's largest encyclopedia -- 9-10-8: eBay-the world's largest online trading community -- 10: Future Of Web Search And Navigation -- Bibliography -- Index.…”
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An introduction to search engines and web navigation / by Levene, M. 1957-

Table of Contents: “…-- 9-1-1: Milgram's small-world experiment -- 9-1-2: Collaboration graphs -- 9-1-3: Instant messaging social network -- 9-1-4: Social Web -- 9-1-5: Social network start-ups -- 9-2: Social network analysis -- 9-2-1: Social network terminology -- 9-2-2: Strength of weak ties -- 9-2-3: Centrality -- 9-2-4: Web communities -- 9-2-5: Pajek: Large network analysis software -- 9-3: Peer-to-peer networks -- 9-3-1: Centralized P2P networks -- 9-3-2: Decentralized P2P networks -- 9-3-3: Hybrid P2P networks -- 9-3-4: Distributed hash tables -- 9-3-5: BitTorrent file distribution -- 9-3-6: JXTA P2P search -- 9-3-7: Incentives in P2P systems -- 9-4: Collaborative filtering -- 9-4-1: Amazon_com -- 9-4-2: Collaborative filtering explained -- 9-4-3: User-based collaborative filtering -- 9-4-4: Item-based collaborative filtering -- 9-4-5: Model-based collaborative filtering -- 9-4-6: Content-based recommendation systems -- 9-4-7: Evaluation of collaborative filtering systems -- 9-4-8: Scalability of collaborative filtering systems -- 9-4-9: Case study of Amazon_co_uk -- 9-4-10: Netflix prize -- 9-4-11: Some other collaborative filtering systems -- 9-5: Weblogs (blogs) -- 9-5-1: Blogrolling -- 9-5-2: Blogspace -- 9-5-3: Blogs for testing machine learning algorithms -- 9-5-4: Spreading ideas via blogs -- 9-5-5: Real-time Web and microblogging -- 9-6: Power-law distributions in the Web -- 9-6-1: Detecting power-law distributions -- 9-6-2: Power-law distributions in the Internet -- 9-6-3: Law of surfing and a law of participation -- 9-6-4: Evolution of the Web via preferential attachment -- 9-6-5: Evolution of the Web as a multiplicative process -- 9-6-6: Evolution of the Web via HOT -- 9-6-7: Small-world networks -- 9-6-8: Robustness and vulnerability of a scale-free network -- 9-7: Searching in social networks -- 9-7-1: Social navigation -- 9-7-2: Social search engines -- 9-7-3: Navigation within social networks -- 9-7-4: Navigation within small-world networks -- 9-7-5: Testing navigation strategies in social networks -- 9-8: Social tagging and bookmarking -- 9-8-1: Flickr-sharing your photos -- 9-8-2: YouTube-broadcast yourself -- 9-8-3: Delicious for social bookmarking -- 9-8-4: Communities within content sharing sites -- 9-8-5: Sharing scholarly references -- 9-8-6: Folksonomy -- 9-8-7: Tag clouds -- 9-8-8: Tag search and browsing -- 9-8-9: Efficiency of tagging -- 9-8-10: Clustering and classifying tags -- 9-9: Opinion mining -- 9-9-1: Feature-based opinion mining -- 9-9-2: Sentiment classification -- 9-9-3: Comparative sentence and relation extraction -- 9-10: Web 2_0 and collective intelligence -- 9-10-1: Ajax -- 9-10-2: Syndication -- 9-10-3: Open APIs, mashups, and widgets -- 9-10-4: Software as a service -- 9-10-5: Collective intelligence -- 9-10-6: Algorithms for collective intelligence -- 9-10-7: Wikipedia-the world's largest encyclopedia -- 9-10-8: eBay-the world's largest online trading community -- 10: Future Of Web Search And Navigation -- Bibliography -- Index.…”
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