List of tables 2.1 Measures assuming binary-valued relevance, where a +b+c+d al number of documents in the corpus 2. 2 User activities which provide feedback 2.3 Or din al scale on which users rank document s 3.1 Topics used for simulation corpus 3.2 The highest-weighted wor ds and their weight s from the user profile after the end of the experiment to find music-related pages. These words have been stemmed, e. g. regga was originally reggae 3.3 Com pari son of n dpm values given different numbers of preferences held by users, after 10 steps of gradient de scent direct ly on the test set 5. 1 Document token dat a structure 100 5.2 Top t wenty words and ted weights from the profile of a collect i agent specializing in cooking. Some of the word endings have been removed(e. g“ min ce”," minced”and" mincing” all become“minc”) t of the st 109 d to adiust profile 146 pics used for news article collection X11List of Tables 2.1 Measures assuming binary-valued relevance, where a + b + c + d = jDj, the total number of documents in the corpus. ............. 32 2.2 User activities which provide feedback. ................. 41 2.3 Ordinal scale on which users rank documents. ............. 41 3.1 Topics used for simulation corpus. ................... 57 3.2 The highest-weighted words and their weights from the user prole after the end of the experiment to nd music-related pages. These words have been stemmed, e.g. regga was originally reggae.. . . . . 62 3.3 Comparison of ndpm values given dierent numbers of preferences held by users, after 10 steps of gradient descent directly on the test set. . . 68 5.1 Document token data structure ..................... 100 5.2 Top twenty words and associated weights from the prole of a collection agent specializing in cooking. Some of the word endings have been removed (e.g., \mince",\minced" and \mincing" all become \minc") or altered (e.g., \parsley" becomes \parslei") as part of the stemming process. .................................. 109 6.1 Parameters used to adjust proles given user actions. ......... 146 6.2 Topics used for news article collection. ................. 149 xiii