Relatedness Measures Research Articles

Measuring Industry Relatedness and Corporate Coherence

Since the seminal contribution of Teece et al. (1994), the strength, scope and quality of corporate diversification is often detected comparing the observed value of some statistics derived from the diversification patterns of a sample of firms, with its expected value. The latter is obtained under a null hypothesis which assumes some random assignment procedure of sectors to firms. The approaches generally adopted in the literature present two problems. First, being based on the observed value of a statistic, these methods could lead, depending on the nature of the sample, to noisy and non-homogeneous estimates. Second, the benchmark value used to identify the presence and strength of deterministic patterns are obtained under specific and privileged null hypothesis. Both effects could lead to the erroneous classification of spurious random effects as deterministic. This paper shows that the adoption of p-scores as measure of relatedness strongly alleviate the first problem, leading to cleaner and more homogeneous estimates. We design and implement a null hypothesis which rules out random artifacts and effectively identify new features in firm diversification pattern. Using the NBER database on patents, we apply our results to the study of the relationship between the coherence and the scope of corporate patent portfolios.

Measuring relatedness between communities in a citation network

As academic disciplines are segmented and specialized, it becomes more difficult to capture relevant research areas precisely by common retrieval strategies using either keywords or journal categories. This paper proposes a method of measuring the relatedness among sets of academic papers in order to detect unrelated communities which are not related to target topic. A citation network, extracted by given keywords, is divided into communities based on the density of links. We measured and compared four measures of relatedness between two communities in a citation network for three large-scale citation datasets. We used both link and semantic similarities. The topological distance from the center in a citation network is a more efficient measure for removing the unrelated communities than the other three measures: the ratio of the number of intercluster links over the all links, the ratio of the number of common terms over all terms, cosine similarity of tf-idf vectors.

Semantic relatedness measurement based on Wikipedia link co‐occurrence analysis

Purpose – Recently, the importance and effectiveness of Wikipedia Mining has been shown in several researches. One popular research area on Wikipedia Mining focuses on semantic relatedness measurement, and research in this area has shown that Wikipedia can be used for semantic relatedness measurement. However, previous methods are facing two problems; accuracy and scalability. To solve these problems, the purpose of this paper is to propose an efficient semantic relatedness measurement method that leverages global statistical information of Wikipedia. Furthermore, a new test collection is constructed based on Wikipedia concepts for evaluating semantic relatedness measurement methods.Design/methodology/approach – The authors' approach leverages global statistical information of the whole Wikipedia to compute semantic relatedness among concepts (disambiguated terms) by analyzing co‐occurrences of link pairs in all Wikipedia articles. In Wikipedia, an article represents a concept and a link to another articl...

Context Disambiguation Based Semantic Web Search for Effective Information Retrieval

Problem statement: Search queries are short and ambiguous and are insufficient for specifying precise user needs. To overcome this problem, some search engines suggest terms that are semantically related to the submitted queries, so that users can choose from the suggestions based on their information needs. Approach: In this study, we introduce an effective approach that captures the user’s specific context by using the WordNet based semantic relatedness measure and the measures of joint keyword occurrences in the web page. Results: The context of the user query is identified and formulated. The user query is enriched to get more relevant web pages that the user needs. Conclusion: Experimental results show that our approach has better precision and recall than the existing methods.

Phylogenetic distance can predict susceptibility to attack by natural enemies

If related species share enemies, variation in the damage experienced by species within a community may be predictable based on phylogeny. We examined the hypothesis that plant species more closely related to other community members experience greater herbivory by assessing leaf damage to native and exotic plants in two North American communities: an Eastern hardwood forest and a Rocky Mountain montane community. Pairwise phylogenetic distances between focal species and the hundreds of other native species in each community were calculated. We examined the influence of four measures of relatedness within each community: NND (phylogenetic distance to the nearest native neighbor), MPD (mean phylogenetic distance to the native species in the community), and two new metrics, MIPD (mean inverse phylogenetic distance) and INND (inverse nearest neighbor distance). These new metrics assume a nonlinear increase in interaction strength with relatedness; in the context of natural enemies, they posit that the sharing of enemies between any two species increases nonlinearly with their relatedness. Using regression models, we found that herbivore damage decreased with decreasing phylogenetic similarity of focal species to native species (as measured by MIPD) in both sites, although the pattern was significant only for native focal species in the montane community and exotic focal species in the hardwood forest. Similar decreases in herbivory with decreasing relatedness were detected using INND (montane natives) and MPD (hardwood forest exotics). There was no significant relationship between NND and herbivory for any of the four site by focal plant origin combinations. Our results are the first to support the hypothesis that native species can escape attack as a function of their phylogenetic dissimilarity to the larger community of native species, and to demonstrate that exotic species show these patterns in the wild (as opposed to in common gardens). We suggest that phylogenetic distance metrics assuming a nonlinear increase in interaction strength with relatedness show promise for broader application.

An empirical comparison of SNPs and microsatellites for parentage and kinship assignment in a wild sockeye salmon (Oncorhynchus nerka) population

Because of their high variability, microsatellites are still considered the marker of choice for studies on parentage and kinship in wild populations. Nevertheless, single nucleotide polymorphisms (SNPs) are becoming increasing popular in many areas of molecular ecology, owing to their high-throughput, easy transferability between laboratories and low genotyping error. An ongoing discussion concerns the relative power of SNPs compared to microsatellites-that is, how many SNP loci are needed to replace a panel of microsatellites? Here, we evaluate the assignment power of 80 SNPs (H(E) = 0.30, 80 independent alleles) and 11 microsatellites (H(E) = 0.85, 192 independent alleles) in a wild population of about 400 sockeye salmon with two commonly used software packages (Cervus3, Colony2) and, for SNPs only, a newly developed software (SNPPIT). Assignment success was higher for SNPs than for microsatellites, especially for parent pairs, irrespective of the method used. Colony2 assigned a larger proportion of offspring to at least one parent than the other methods, although Cervus and SNPPIT detected more parent pairs. Identification of full-sib groups without parental information from relatedness measures was possible using both marker systems, although explicit reconstruction of such groups in Colony2 was impossible for SNPs because of computation time. Our results confirm the applicability of SNPs for parentage analyses and refute the predictability of assignment success from the number of independent alleles.

Testing Darwin’s naturalization hypothesis in the Azores

Invasive species are a threat for ecosystems worldwide, especially oceanic islands. Predicting the invasive potential of introduced species remains difficult, and only a few studies have found traits correlated to invasiveness. We produced a molecular phylogenetic dataset and an ecological trait database for the entire Azorean flora and find that the phylogenetic nearest neighbour distance (PNND), a measure of evolutionary relatedness, is significantly correlated with invasiveness. We show that introduced plant species are more likely to become invasive in the absence of closely related species in the native flora of the Azores, verifying Darwin's 'naturalization hypothesis'. In addition, we find that some ecological traits (especially life form and seed size) also have predictive power on invasive success in the Azores. Therefore, we suggest a combination of PNND with ecological trait values as a universal predictor of invasiveness that takes into account characteristics of both introduced species and receiving ecosystem.

Using ontological and document similarity to estimate museum exhibit relatedness

Exhibits within cultural heritage collections such as museums and art galleries are arranged by experts with intimate knowledge of the domain, but there may exist connections between individual exhibits that are not evident in this representation. For example, the visitors to such a space may have their own opinions on how exhibits relate to one another. In this article, we explore the possibility of estimating the perceived relatedness of exhibits by museum visitors through a variety of ontological and document similarity-based methods. Specifically, we combine the Wikipedia category hierarchy with lexical similarity measures, and evaluate the correlation with the relatedness judgements of visitors. We compare our measure with simple document similarity calculations, based on either Wikipedia documents or Web pages taken from the Web site for the museum of interest. We also investigate the hypothesis that physical distance in the museum space is a direct representation of the conceptual distance between exhibits. We demonstrate that ontological similarity measures are highly effective at capturing perceived relatedness and that the proposed RACO (Related Article Conceptual Overlap) method is able to achieve results closest to relatedness judgements provided by human annotators compared to existing state-of-the art measures of semantic relatedness.

Ontology-based semantic relatedness for detecting the relevance of learning resources

Semantic relatedness measures have proven useful for a number of applications, such as querying personalized web resources, word sense disambiguation, or real-word spelling error correction. Most semantic relatedness measures between concepts are based on the concept hierarchy of a domain ontology. In this article, we propose a semantic relevance (SR) measure that expresses the semantic relatedness between a learning resource and the learning context of a learner. In our case, both the learning resource and the learning context are described by graphs using the learning concepts of the domain model. Our SR measure aims to detect the relevance of a learning resource for a particular learning context of a learner. In our work, the SR measure is based on the assignment of relative weights to the learning concepts describing the learning resource according to their relationships with the current concept of interest to the learner. The proposed measure achieves better results than the relatedness measures from the literature and yet is much simpler than most of them. It is shown to achieve a correlation of from 0.627 to 0.945 with expert ratings. This measure is implemented and used in a learning organizer, a system which generates adaptive hypermedia courses and reuses learning resources from distant web repositories, called Organisateur de Parcours Adaptatifs de Formation (OrPAF). In OrPAF, learning resources are annotated in order to be queried for a particular learning context, which is represented by a map of annotated learning concepts, called an adaptive conceptual map. The proposed SR measure is used in order to automatically detect the learning resource relevance.

Asymmetry in corpus-derived and human word associations

We investigate asymmetry in corpus-derived and human word associations. Most prior work has studied paradigmatic relations, either derived from free association norms or from large corpora using measures of statistical association and semantic relatedness. By contrast, we investigate the syntagmatic relation between words in adjective-noun and noun-noun combinations and present a new experimental design for measuring the strength of human associations. Of particular importance for syntagmatic relations are asymmetric associations, whose associational strength is much larger in one direction (e.g., from Pyrrhic to victory) than in the other (e.g., from victory to Pyrrhic). We develop a number of corpus-derived measures of asymmetric association and show that they predict the directedness of human associations with high accu-

Can the Survivor Principle Survive Diversification?

The survivor principle holds that the competitive process weeds out inefficient firms, so that hypotheses about efficient behavior can be tested by observing how firms actually behave. This principle underlies a large body of empirical work in strategy, economics, and management. But do competitive markets actually display what is efficient? Is the survivor principle reliable? We evaluate the survivor principle in the context of corporate diversification, showing that survivor-based measures of inter-industry relatedness are good predictors of firm’s decisions to exit particular lines of business, even when controlling for other firm and industry characteristics that affect the decision to withdraw from one industry or another. We argue further that his relatedness measure captures an important aspect of economic efficiency, not simply firms’ desire for legitimacy by imitation, or attempts to temper multi-market competition. Hence confidence in the survivor principle is warranted, at least in this context.

Characterizing allelic association in the genome era.

Whole genome data are allowing the estimation of population genetic parameters with an accuracy not imagined 50 years ago. Variation in these parameters along the genome is being found empirically where once only approximate theoretical values were available. Along with increased information, however, has come the issue of multiple testing and the realization that high values of the coefficients of variation of quantities such as relatedness measures may make it difficult to draw inferences. This review concentrates on measures of allelic association within and between individuals and within and between populations.

Towards a framework for developing semantic relatedness reference standards

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results. Our proposed framework is based on the experiences of medical informatics and computational linguistics communities and addresses practical and theoretical issues with creating reference standards for semantic relatedness. We demonstrate the use of the framework on a pilot set of 101 medical term pairs rated for semantic relatedness by 13 medical coding experts. While the reliability of this particular reference standard is in the “moderate” range; we show that using clustering and factor analyses offers a data-driven approach to finding systematic differences among raters and identifying groups of potential outliers. We test two ontology-based measures of relatedness and provide both the reference standard containing individual ratings and the R program used to analyze the ratings as open-source. Currently, these resources are intended to be used to reproduce and compare results of studies involving computerized measures of semantic relatedness. Our framework may be extended to the development of reference standards in other research areas in medical informatics including automatic classification, information retrieval from medical records and vocabulary/ontology development.

An Information-Theoretic Foundation for the Measurement of Discrimination Information

Hitherto, it has not been easy to interpret the meaning of the amount of discrimination information conveyed in a term rationally and explicitly within practical application contexts; it has not been simple to introduce the concept of the extent of semantic relatedness between two terms meaningfully and successfully into scientific discussions. This study is part of an attempt to do this. We attempt to answer two important questions: (1) What is the discrimination information conveyed by a term and how to measure it? (2) What is the relatedness between two terms and how to estimate it? We focus on the first question and present an in-depth investigation into the discrimination measures based on several information measures, which are widely used in a variety of applications. The relatedness measures are then naturally defined according to the individual discrimination measures. Some key points are made for clarifying potential problems arising from using the relatedness measures, and solutions are suggested. Two example applications in the contexts of text mining and information retrieval are provided. The aim of this study, of which this paper forms part, is to establish a unified theoretical framework, with measurement of discrimination information (MDI) at the core, for achieving effective measurement of semantic relatedness (MSR). Due to its generality, our method can be expected to be a useful tool with a wide range of application areas.

Inclusive Fitness from Multitype Branching Processes

Iuse multitype branching processes to study genetic models for the evolution of social behaviour, i.e. behaviours that, when acted out, affect the success of the actor's neighbours. Here, Isuppose an individual bearing a mutant copy of a gene influences the reproductive success of a neighbour by altering its own competitive ability. Approximations based on assumptions about the rareness of the mutant allele and the strength of selection allow me to formulate statements concerning the probability of mutant extinction in terms of inclusive fitness. Inclusive fitness is an idea well known to biologists and can be thought of as a sum of an individual's fitness and the fitness of each of its relatives, weighted by some measure of genetic relatedness. Previous work has led to some confusion surrounding the definition of the inclusive-fitness effect of a mutant allele when individuals carrying that allele experience demographic conditions that fluctuate randomly. In this paper, I emphasise the link between inclusive fitness and the probability of mutant extinction. I recover standard results for populations of constant size, and I show that inclusive fitness can be used to determine the short-term fate of mutants in the face of stochastic demographic fluctuations. Overall, then, I provide a connection between certain inclusive-fitness-based approaches routinely applied in theoretical studies of social evolution.

Celerinatantimonas diazotrophica gen. nov., sp. nov., a nitrogen-fixing bacterium representing a new family in the Gammaproteobacteria, Celerinatantimonadaceae fam. nov.

Five strains representing a novel family within the Gammaproteobacteria were isolated from the estuarine grasses Spartina alterniflora and Juncus roemerianus. All strains were facultatively anaerobic, Gram-negative, short, motile, polar monotrichous rods that were mesophilic, oxidase-negative, catalase-positive, had DNA G+C contents of 41.5-44.4 mol% and required seawater salts or NaCl. Growth was observed at pH 3.5-8.0. Polar lipids diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, phosphatidylmonomethylethanolamine, aminophospholipid, phospholipids and unidentified aminolipids were found in the representative strain S-G2-2(T). The major menaquinone and ubiquinone were MK-8 (100 %) and Q-8 (93 %), respectively. Predominant fatty acids present were C(12 : 0) aldehyde and/or unknown fatty acid 10.9525 (MIDI designation) and/or iso-C(16 : 1) I/C(14 : 0) 3-OH, C(16 : 1)ω7c/C(16 : 1)ω6c, C(16 : 0), C(17 : 0) cyclo and C(18 : 1)ω7c and/or C(18 : 1)ω6c. The nearly full-length 16S rRNA gene sequences of the strains were very similar (99-100 % similarity), and the strains were identified as members of the same species by DNA-DNA relatedness measurements. 16S rRNA gene sequence analysis revealed that the strains formed a monophyletic lineage within the order Alteromonadales. All five strains fixed N(2). Analysis of partial nifH gene sequences also revealed a monophyletic lineage within the Gammaproteobacteria, and the sequences were dissimilar to those of any previously described diazotroph. Differences between the novel strains and other members of the Alteromonadales include the inability to produce cytochrome oxidase. The novel strains were metabolically versatile. On the basis of the information described above, the new genus and species Celerinatantimonas diazotrophica gen. nov., sp. nov. are proposed to accommodate the five strains within a new family, Celerinatantimonadaceae fam. nov. The type strain of Celerinatantimonas diazotrophica is S-G2-2(T) ( = ATCC BAA-1368(T) = DSM 18577(T)).

Reciprocal effects of student–teacher and student–peer relatedness: Effects on academic self efficacy

This study investigated the reciprocal effects between teacher–student relationship quality (TSRQ) and two dimensions of classroom peer relatedness, peer liking and peer academic reputation (PAR), across three years in elementary school and the effect of both TSRQ and the peer relatedness dimensions on academic self efficacy. Participants were 695 relatively low achieving, ethnically diverse students recruited into the longitudinal study when they were in the first grade. Measures of TSRQ and peer relatedness were assessed in years/grades 2–4. Peer liking and PAR were moderately correlated with each other at each time period. As expected, peer liking and TSRQ exhibited bidirectional effects across the three years. Year 3 TSRQ had an effect on Year 4 PAR, but PAR did not have an effect on TSRQ at either time interval. In an additional analysis, Year 4 PAR mediated the effect of Year 3 TSRQ on Year 5 academic self efficacy. Implications for teacher professional development are discussed.

Co-citations as citation endorsements and co-links as link endorsements

Co-citations and co-links have long been used as measures of topical relatedness between documents in various datasets. However, there are some characteristic differences between co-citations in scientific literature and co-links in hypertext due to the underlying difference in the motivations for creating citations and links. While citations are created for formal scholarly communication, links are created for a variety of formal as well as informal purposes. We elaborate on these differences, and propose interpretations of a co-citation as an endorsement of a citation, and a co-link as an endorsement of a link. Such an interpretation is useful for focused or topical surfers to follow citations and links that are pertinent to a topic of interest in scientific literature and the web respectively.

The Swedish Arctic charr breeding programme

Results and experiences from a selective breeding programme aiming at improving the performance of an Arctic charr strain in aquaculture are presented. The programme, which has been running since 1985, uses traditional quantitative genetic methods based on relatedness and trait measurements. Traits considered included growth, age at sexual maturity, flesh colour, fat content and other features. Estimates in the early phase of the programme showed promising heritabilities for most traits, e.g. growth heritabilities of 0.34–0.52, and suggested that improvement by selection was feasible. Several traits such as a high rate of early maturation and poor flesh colour that were considered problematic by the Arctic charr farming industry at the programme’s start no longer hamper farming. Considerable improvement of growth by selection, estimated at 8% per generation, has contributed to shortening the production cycle in commercial farming. Results from studies of genotype–environment interactions are presented and discussed. Poor survival of fertilised eggs is a major problem in Swedish Arctic charr farming as indicated by presented survival rates. Efforts have consistently been made to avoid inbreeding in the selected strain, and at the present seventh generation the accumulated increase in inbreeding is estimated from pedigree data to be only approximately 5%.

Comparing Transcription Rate and mRNA Abundance as Parameters for Biochemical Pathway and Network Analysis

The cells adapt to extra- and intra-cellular signals by dynamic orchestration of activities of pathways in the biochemical networks. Dynamic control of the gene expression process represents a major mechanism for pathway activity regulation. Gene expression has thus been routinely measured, most frequently at steady-state mRNA abundance level using micro-array technology. The results are widely used in statistical inference of the structures of underlying biochemical networks, with the assumption that functionally related genes exhibit similar dynamic profiles. Steady-state mRNA abundance, however, is a composite of two factors: transcription rate and mRNA degradation rate. The question being asked here is therefore whether steady-state mRNA abundance or any of two factors is a more informative measurement target for studying network dynamics. The yeast S. cerevisiae was used as model organism and transcription rate was chosen out of the two factors in this study, because genome-wide determination of transcription rates has been reported for several physiological processes in this species. Our strategy is to test which one is a better measurement of functional relatedness between genes. The analysis was performed on those S. cerevisiae genes that have bacterial orthologs as identified by reciprocal BLAST analysis, so that functional relatedness of a gene pair can be measured by the frequency at which their bacterial orthologs co-occur in the same operon in the collection of bacterial genomes. It is found that transcription rate data is generally a better parameter for functional relatedness than steady state mRNA abundance, suggesting transcription rate data is more informative to use in deciphering the logics used by the cells in dynamic regulation of biochemical network behaviors. The significance of this finding for network and systems biology, as well as biomedical research in general, is discussed.