Tackling redundancy in text summarization through different levels of language analysis

One of the main challenges to be addressed in text summarization concerns the detection of redundant information. This paper presents a detailed analysis of three methods for achieving such goal. The proposed methods rely on different levels of language analysis: lexical, syntactic and semantic. Moreover, they are also analyzed for detecting relevance in texts. The results show that semantic-based methods are able to detect up to 90% of redundancy, compared to only the 19% of lexical-based ones. This is also reflected in the quality of the generated summaries, obtaining better summaries when employing syntactic- or semantic-based approaches to remove redundancy.

MGOF: Stata module to perform goodness-of-fit tests for multinomial data

mgof computes goodness-of-fit tests for the distribution of a discrete (categorical, multinomial) variable. The default is to perform classical large sample chi-squared approximation tests based on Pearson's X2 statistic and the log likelihood ratio (G2) statistic or a statistic from the Cressie-Read family. Alternatively, mgof computes exact tests using Monte Carlo methods or exhaustive enumeration. A Kolmogorov-Smirnov test for discrete data is also provided. The moremata package, also available from SSC, is required.

Multinomial goodness-of-fit: large sample tests with survey design correction and exact tests for small samples

A new Stata command called -mgof- is introduced. The command is used to compute distributional tests for discrete (categorical, multinomial) variables. Apart from classic large sample $\chi^2$-approximation tests based on Pearson's $X^2$, the likelihood ratio, or any other statistic from the power-divergence family (Cressie and Read 1984), large sample tests for complex survey designs and exact tests for small samples are supported. The complex survey correction is based on the approach by Rao and Scott (1981) and parallels the survey design correction used for independence tests in -svy:tabulate-. The exact tests are computed using Monte Carlo methods or exhaustive enumeration. An exact Kolmogorov-Smirnov test for discrete data is also provided.

Value Creation in Family Firms: A Model of Fit

We propose a framework describing how family ownership can create or destroy value depending on the goals, resources, and governance of the family firm, which are each influenced by the family owners. Taking a contingency perspective, we suggest that a fit is required for all three elements – family- influenced goals, resources, and governance – for the family firm to flourish over generations. We conclude with a suggested research agenda indicating research opportunities at the nexus of these identified elements. Further we provide some guiding questions for practitioners that might stimulate fruitful discussions among family firm owners and managers about how to realize ‘‘fit.’’

Agricultural development of Panama; analysis of current problems and recommendations for a program.

Cover title.

Evaluation of diagnostic analysis and test equipment for small automotive repair establishments. A report to the Congress.

Mode of access: Internet.

The larger forms of musical composition; an exhaustive explanation of the variations, rondos, and sonata designs, for the general student of musical analysis, and for the special student of structural composition,

"A sequel to the Homophonic forms and Applied counterpoint."--Pref.

The structure of American economy, 1919-1929 : an empirical application of equilibrium analysis /

Bibliographical references in "Statistical sources and methods of computation" (p.[141]-162.)

Axis rule in occupied Europe : laws of occupation, analysis of government, proposals for redress /

Bibliography: p. 641-651.