[PDF] Top 20 Tweet Recommendation with Graph Co Ranking

... same recommendation lists for all users. Our co-ranking algorithm models user interest with respect to the content of the tweets and their pub- ... See full document

... with graph co- ...heterogeneous graph to model two types of relations, including seman- tic relations and opinion ...a co-ranking algorithm is proposed to es- timate the confidence of ... See full document

... and graph ranking ...solution graph. These links also allow us to build up statistical co-occurrence counts between entities that occur in the same context which may be used to weight links in ... See full document

... knowledge graph embedding mod- els have been developed to populate knowl- edge graphs and these have shown outstand- ing ...knowledge graph embedding models are so-called black boxes, and the user does not ... See full document

... particular ranking scenario where the click-through data is sparse and ...Click-Boosted Graph Ranking (CBGR) approach for effective image retrieval based on a preliminary work [12], which ... See full document

... of graph-based ranking algorithms to the tag recommendation problem in ...widely-used graph model of the folksonomy as well as FolkRank’s weight spreading ...improved graph model that ... See full document

... word co-occurrences and reinforce edge weights in the word ...Borrowing co- occurrence information from multiple documents, their approach improves the word ranking perfor- ... See full document

... the graph with co-occurrence information borrowed from similar ...the graph and reinforce the weight of existing ...each graph and to merge the rankings ... See full document

... Instead, the confidence of each candidate is estimated by the global random walk process with the graph co- ranking. Intuitively, the error propagation is effectively alleviated [18]. The WAM should ... See full document

... each tweet a relevance score based on different factors relating to tweet, author of the tweet and the user whose timeline is ...on ranking tweets based on these trending ...hashtag ... See full document

... or graph-based re-ranking models (Cucerzan, 2007; Milne and Witten, 2008b; Han and Zhao, 2009; Kulkarni et ...novel graph representation with fine-grained relations, (ii) A unified frame- work based ... See full document

... In phrase Reinforcement algorithm it begins with a starting phase which is the topic for which one desired to generate summary sometimes these are trending topic but can be other non-trending topics as well for the ... See full document

... session-based recommendation, the work of (Hidasi et ...and co-occurrence ...list-wise ranking model to generate the recommendation for each ...tentive recommendation machine with an ... See full document

... is Graph-based opinion entity ranking framework which is used to mine opinion data fro m former customers and rank their entities or aspects in accordance with those ...bipartite graph and an ... See full document

... novel recommendation service using a unique group ranking se- quence technique “Mining Maximum Consensus Sequences from all Users’ Partial Ranking Lists ...group ranking sequence ... See full document

... Collaborative Filtering (CF) techniques, some of them applied content-based approach, and a few of them combined CF approach with content-based techniques. Quality-of-Service (QoS) is widely employed to represent the ... See full document

... Feature recovery is possible by positioning the examples as indicated by their likelihood scores that were anticipated by classifiers. It is frequently conceivable to enhance the recovery execution by re-positioning the ... See full document

... A tweet is a short text message containing no more than 140 ...the tweet; words starting with “@", like “@office" and “@momtobedby8", represent user names, and ... See full document

... The six automatic summarization algorithms are implemented in [9], for finding similar Thai tweets. The experimental results showed that Text Rank algorithm performed the best because this algorithm selected the tweets ... See full document

... outperforms the baselines both on AUC and MAP. More- over, users usually check a few top-ranked items in real- world applications, top-K evaluation metrics are important for studying the recommendation ... See full document