FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W177807718> ?p ?o ?g. }

• W177807718 abstract "Statistical Relational Learning is a new branch of machine learning that aims to model a joint distribution over relational data. Relational data consists of different types of objects where each object is characterized with a different set of attributes. The structure of relational data presents an opportunity for objects to carry additional information via their links and enables the model to show correlations among objects and their relationships. This dissertation focuses on learning graphical models for such data. Learning graphical models for relational data is much more challenging than learning graphical models for propositional data. One of the challenges of learning graphical models for relational data is that relational data, unlike propositional data, is non independent and identically distributed and cannot be viewed in a single table. Relational data can be modeled using a graph, where objects are the nodes and relationships between the objects are the edges. In this graph, there may be multiple edges between two nodes because objects may have different types of relationships with each other. The existence of multiple paths of different length among objects makes the learning procedure much harder than learning from a single table. We use a lattice search approach with lifted learning to deal with the multiple path problem. We focus on learning the structure of Markov Logic Networks, which are a first order extension of Markov Random Fields. Markov Logic Networks are a prominent undirected statical relational model that have achieved impressive performance on a variety of statistical relational learning tasks. Our approach combines the scalability and efficiency of learning in directed relational models, and the inference power and theoretical foundations of undirected relational models. We utilize an extension of Bayesian networks based on first order logic for learning class-level or first-order dependencies, which model the general database statistics over attributes of linked objects and their links. We then convert this model to a Markov Logic Network using the standard moralization procedure. Experimental" @default.
• W177807718 created "2016-06-24" @default.
• W177807718 creator A5007067645 @default.
• W177807718 date "2012-10-12" @default.
• W177807718 modified "2023-09-27" @default.
• W177807718 title "Directed Models For Statistical Relational Learning" @default.
• W177807718 cites W127700604 @default.
• W177807718 cites W1458239765 @default.
• W177807718 cites W1487276429 @default.
• W177807718 cites W1487588218 @default.
• W177807718 cites W1504069565 @default.
• W177807718 cites W1506285740 @default.
• W177807718 cites W1509515766 @default.
• W177807718 cites W1516145264 @default.
• W177807718 cites W1517512971 @default.
• W177807718 cites W1517993545 @default.
• W177807718 cites W1524326598 @default.
• W177807718 cites W1535439311 @default.
• W177807718 cites W1544444076 @default.
• W177807718 cites W155535615 @default.
• W177807718 cites W1559060276 @default.
• W177807718 cites W1560512119 @default.
• W177807718 cites W1563726162 @default.
• W177807718 cites W1584654272 @default.
• W177807718 cites W1585529040 @default.
• W177807718 cites W1588527235 @default.
• W177807718 cites W1594170653 @default.
• W177807718 cites W1605586974 @default.
• W177807718 cites W1615454278 @default.
• W177807718 cites W1666347389 @default.
• W177807718 cites W1805906695 @default.
• W177807718 cites W1860991815 @default.
• W177807718 cites W193724012 @default.
• W177807718 cites W1961449491 @default.
• W177807718 cites W1965552673 @default.
• W177807718 cites W1974362060 @default.
• W177807718 cites W1974865846 @default.
• W177807718 cites W1975130368 @default.
• W177807718 cites W1983661866 @default.
• W177807718 cites W1983690667 @default.
• W177807718 cites W1984374364 @default.
• W177807718 cites W1986832527 @default.
• W177807718 cites W1996824494 @default.
• W177807718 cites W2000805332 @default.
• W177807718 cites W2002826893 @default.
• W177807718 cites W2006912660 @default.
• W177807718 cites W2021602734 @default.
• W177807718 cites W2023719154 @default.
• W177807718 cites W2028137574 @default.
• W177807718 cites W203049729 @default.
• W177807718 cites W2033072307 @default.
• W177807718 cites W2049633694 @default.
• W177807718 cites W2065606385 @default.
• W177807718 cites W2069150044 @default.
• W177807718 cites W2072100806 @default.
• W177807718 cites W2073171642 @default.
• W177807718 cites W2080828514 @default.
• W177807718 cites W2083568285 @default.
• W177807718 cites W2101705355 @default.
• W177807718 cites W2101736851 @default.
• W177807718 cites W2101782549 @default.
• W177807718 cites W2112492108 @default.
• W177807718 cites W2118440866 @default.
• W177807718 cites W2119174985 @default.
• W177807718 cites W2120976331 @default.
• W177807718 cites W2121075864 @default.
• W177807718 cites W2122410182 @default.
• W177807718 cites W2123827533 @default.
• W177807718 cites W2125027602 @default.
• W177807718 cites W2126185296 @default.
• W177807718 cites W2127345773 @default.
• W177807718 cites W2133990480 @default.
• W177807718 cites W2135863341 @default.
• W177807718 cites W2137027418 @default.
• W177807718 cites W2139192394 @default.
• W177807718 cites W2141518341 @default.
• W177807718 cites W2142857211 @default.
• W177807718 cites W2144429462 @default.
• W177807718 cites W2144461918 @default.
• W177807718 cites W2149706766 @default.
• W177807718 cites W2150010872 @default.
• W177807718 cites W2150475393 @default.
• W177807718 cites W2150678881 @default.
• W177807718 cites W2162188273 @default.
• W177807718 cites W2163738067 @default.
• W177807718 cites W2168865746 @default.
• W177807718 cites W2169992051 @default.
• W177807718 cites W2175160295 @default.
• W177807718 cites W2401098482 @default.
• W177807718 cites W2525811808 @default.
• W177807718 cites W2540540486 @default.
• W177807718 cites W2551661310 @default.
• W177807718 cites W2795840897 @default.
• W177807718 cites W28766783 @default.
• W177807718 cites W2914587038 @default.
• W177807718 cites W2914983426 @default.
• W177807718 cites W2962735828 @default.
• W177807718 cites W2982977987 @default.
• W177807718 cites W3022603917 @default.
• W177807718 cites W46452414 @default.

• next