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COMS 6998-06 Network Theory Week 7. Dragomir R. Radev Wednesdays, 6:10-8 PM 325 Pupin Terrace Fall 2010. (17) Lexical networks. Free word associations. The large-scale structure of semantic networks: statistical analyses and a model of semantic growth M. Steyvers, J. B. Tenenbaum (2005)
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COMS 6998-06 Network TheoryWeek 7 Dragomir R. Radev Wednesdays, 6:10-8 PM 325 Pupin Terrace Fall 2010
Free word associations The large-scale structure of semantic networks: statistical analyses and a model of semantic growth M. Steyvers, J. B. Tenenbaum (2005) Cognitive Science, 29(1)
Dependency network bought Meredith yesterday apples green
Language networks • A special case of networks where nodes are words or documents and edges link semantically related nodes • Other examples: • Words used in dictionary definitions • Names of people mentioned in the same story • Words that translate to the same word
Some real networks • From Newman 2002:
universe letter character nature world actor Properties of lexical networks • Entries in a thesaurus[Motter et al. 2002] • c/c0 = 260 (n=30,244; m=60) • Co-occurrence networks [Dorogovtsev and Mendes 2001, Sole and Ferrer i Cancho 2001] • c/c0 = 1,000 (n=400,000) • Mental lexicon [Vitevitch 2005] • c/c0 = 278 (n=19,340)
Sigman and Cecchi 2002 • Meronymy • Component (branch-tree) • Member (tree-forest) • Stuff (glass-bottle) • Polysemy • E.g., board • Hypernymy/hyponymy • E.g., oak-tree
n=8,992 m=117,687 alpha = 1.1 Masucci and Rodgers 2006 It was a bright cold day in April, and the clocks were striking thirteen. Winston Smith, his chin nuzzled into his breast in an effort to escape the vile wind, slipped quickly through the glass doors of Victory Mansions, though not quickly enough to prevent a swirl of gritty dust from entering along with him. The hallway smelt of boiled cabbage and old rag mats. At one end of it a coloured poster, too large for indoor display, had been tacked to the wall. It depicted simply an enormous face, more than a metre wide: the face of a man of about forty-five, with a heavy black moustache and ruggedly handsome features. Winston made for the stairs. It was no use trying the lift. Even at the best of times it was seldom working, and at present the electric current was cut off during daylight hours. It was part of the economy drive in preparation for Hate Week. The flat was seven flights up, and Winston, who was thirty-nine and had a varicose ulcer above his right ankle, went slowly, resting several times on the way. On each landing, opposite the lift-shaft, the poster with the enormous face gazed from the wall. It was one of those pictures which are so contrived that the eyes follow you about when you move. BIG BROTHER IS WATCHING YOU, the caption beneath it ran.
Lexical centrality • In social networks, some people are called mavens/centers due to their popularity (or gregariousness) • What is the analog to a highly connected person in a language network? • In general, how can network structure be used to identify content in a language network?
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List of topics • Red Sox • Sweep • World Series • Rockies • Celebrate • Boston • Colorado • Dynasty • 2007 • Four years • Second time • 4:3 score • Easy • Expectations • No curse • Young players • Timlin • not (baseball)
LexRank – Centrality in Text Graphs Vertices Units of text (sentences or documents) Edges Pairwise similarity between text (tf-idf cosine or language model)
LexRank – Centrality in Text Graphs Intuition LexRank score is propagated through edges Central vertices are those that are similar to other central vertices
LexRank – Centrality in Text Graphs Recurrence Relation 0.3 0.1 0.9 0.3 s 0.5 0.8 Can guarantee solution by allowing “jump” probability d/N. 0.2 0.4 0.2
0.01718 Red Sox Win Baseball's World Series Title by Sweeping Rockies 0.01712 Red Sox Sweep Rockies To Win World Series 0.01647 World Series: Red Sox sweep Rockies 0.01630 Red Sox sweep Rockies, take World Series 0.01608 Red Sox 4, Rockies 3 Boston Sweeps World Series Again 0.01597 World Series: Red Sox complete sweep of Rockies 0.01584 Red Sox sweep World Series 0.01579 Red Sox Sweep Colorado in World Series 0.01573 Red Sox Complete Sweep Of Rockies For World Series Victory 0.01531 Red Sox complete World Series sweep ... 0.01057 Boston Red Sox blank Rockies to clinch World Series 0.01052 Red Sox: Dynasty in the making 0.01037 Sox sweep Rockies for 2nd title in 4 seasons 0.01034 Police Arrest Dozens After Red Sox World Series Win 0.01027 Rookies respond in first crack at the big time 0.01018 Rockies: Sweep, sweep, swept 0.01016 Sweeping off to Boston 0.01013 Rookies rise to occasion! 0.01012 Fans celebrate Red Sox win 0.01010 Short wait for bosox this time ... 0.00441 Sox are kings of diamond 0.00414 Rockies just failed to execute 0.00408 Rockies Find Being Good Isnt Enough 0.00407 Rockies' heads held high despite loss 0.00391 Boston lowers the broom 0.00390 Rockies Vanish In Thin Air 0.00390 Poor pitching, poorer hitting doom Rockies 0.00390 Rockies feel the pain, but not the shame 0.00375 Two titles four years apart impossible to compare 0.00362 Boston reigns supreme
0.01718 Red SoxWin Baseball's World Series Title by Sweeping Rockies 0.01712 Red Sox Sweep Rockies To Win World Series 0.01647 World Series: Red Sox sweep Rockies 0.01630 Red Sox sweep Rockies, take World Series 0.01608 Red Sox 4, Rockies 3 Boston Sweeps World Series Again 0.01597 World Series: Red Sox complete sweep of Rockies 0.01584 Red Sox sweepWorld Series 0.01579 Red Sox Sweep Colorado in World Series 0.01573 Red Sox Complete Sweep Of Rockies For World Series Victory 0.01531 Red Sox complete World Series sweep ... 0.01057 Boston Red Soxblank Rockies to clinch World Series 0.01052 Red Sox: Dynasty in the making 0.01037 Sox sweep Rockies for 2nd title in 4 seasons 0.01034 Police Arrest Dozens After Red Sox World Series Win 0.01027 Rookies respond in first crack at the big time 0.01018 Rockies: Sweep, sweep, swept 0.01016 Sweeping off to Boston 0.01013 Rookies rise to occasion! 0.01012 Fans celebrate Red Sox win 0.01010 Short wait for bosox this time ... 0.00441 Sox are kings of diamond 0.00414 Rockies just failed to execute 0.00408 Rockies Find Being Good Isnt Enough 0.00407 Rockies' heads held high despite loss 0.00391 Boston lowers the broom 0.00390 Rockies Vanish In Thin Air 0.00390 Poor pitching, poorer hitting doom Rockies 0.00390 Rockies feel the pain, but not the shame 0.00375 Two titles four years apart impossible to compare 0.00362 Boston reigns supreme
Stationary solutions • The fundamental Ergodic Theorem for Markov chains [Grimmett and Stirzaker 1989] says that the Markov chain with kernel E has a stationary distribution p under three conditions: • E is stochastic • E is irreducible • E is aperiodic • To make these conditions true: • All rows of E add up to 1 (and no value is negative) • Make sure that E is strongly connected • Make sure that E is not bipartite • Example: PageRank [Brin and Page 1998]: use “teleportation”
d3s3 d2s3 d3s2 d3s1 d1s1 d4s1 d5s1 d2s1 d5s2 d5s3 d2s2 Lexical centrality (t=0.3)
d3s3 d2s3 d3s2 d3s1 d1s1 d4s1 d5s1 d2s1 d5s2 d5s3 d2s2 Lexical centrality (t=0.2)
d3s2 d3s3 d2s3 d3s2 d4s1 d3s1 d2s1 d1s1 d4s1 d5s1 d2s1 d5s2 d5s3 d2s2 Lexical centrality (t=0.1) Sentences vote for the most central sentence! Need to worry about diversity reranking.
DUC 2004 results Content-based evaluation (ROUGE)
Latent networks • When there is no explicit network, we can create one. • Latent networks – generating functions for networks. • Complex system with one parameter (akin to temperature). • With a change in temperature, latent links become active (or inactive). • Examples: social network in a small town; network of business connections. • Looking for phase transitions.
ap158 degree t cutoff counts