Multiple Types Of Relationships Research Articles

Extracting relations from traditional Chinese medicine literature via heterogeneous entity networks.

Traditional Chinese medicine (TCM) is a unique and complex medical system that has developed over thousands of years. This article studies the problem of automatically extracting meaningful relations of entities from TCM literature, for the purposes of assisting clinical treatment or poly-pharmacology research and promoting the understanding of TCM in Western countries. Instead of separately extracting each relation from a single sentence or document, we propose to collectively and globally extract multiple types of relations (eg, herb-syndrome, herb-disease, formula-syndrome, formula-disease, and syndrome-disease relations) from the entire corpus of TCM literature, from the perspective of network mining. In our analysis, we first constructed heterogeneous entity networks from the TCM literature, in which each edge is a candidate relation, then used a heterogeneous factor graph model (HFGM) to simultaneously infer the existence of all the edges. We also employed a semi-supervised learning algorithm estimate the model's parameters. We performed our method to extract relations from a large dataset consisting of more than 100,000 TCM article abstracts. Our results show that the performance of the HFGM at extracting all types of relations from TCM literature was significantly better than a traditional support vector machine (SVM) classifier (increasing the average precision by 11.09%, the recall by 13.83%, and the F1-measure by 12.47% for different types of relations, compared with a traditional SVM classifier). This study exploits the power of collective inference and proposes an HFGM based on heterogeneous entity networks, which significantly improved our ability to extract relations from TCM literature.

Non-parental adults in the social and risk behavior networks of sexual minority male youth

The presence of non-parental adults (NPAs), or adults outside of caregivers (e.g., extended family and natural mentors), in the lives of adolescents and emerging adults has received a rapidly expanding amount of empirical attention in the last decade. Compared to their heterosexual counterparts, sexual minority male youth (SMMY) experience disproportionate rates of abuse and victimization from parents and peers. Yet, despite the fact that this group, therefore, may be potentially vulnerable to negative interpersonal influences but also poised to benefit from additional relationships, NPA involvement in the lives of SMMY is currently not well understood in the extant literature. This study sought to examine and characterize the involvement of NPAs in the social and risk networks of SMMY (n=175; 54% African American, 21% Hispanic/Latino, 14% Caucasian; ages: 17–23). Most SMMY identified at least one NPA, such as friends and grandparents, in their networks. Three categories of relationships were identified, Strictly Social, which only involved social interactions; Complex, which were both social and involved substance use and/or sexual activity; and Risky, which purely consisted of substance use or sexual activity. Relationships were rated as emotionally “closer” among ethnic minority SMMY, although, racial/ethnic similarity between SMMY and NPAs was not associated with relationship closeness. In addition, relationships involving female and heterosexual NPAs were also rated as stronger. These findings suggest the potential usefulness of considering multiple types of relationships between SMMY and NPAs when designing intervention and prevention efforts. Moreover, African American and Latino SMMY, who represent the most vulnerable sub-groups of SMMY in terms of HIV-risk, may be particularly poised to benefit from positive NPA relationships.

Co-father relationships among the Suruí (Paiter) of Brazil.

Partible paternity refers to the conception belief that children can have multiple fathers (“co-fathers”) and is common to indigenous cultures of lowland South America. The nature of social relationships observed between co-fathers reveals information about the reproductive strategies underlying partible paternity. Here we analyze clan, genealogical, and social relationships between co-fathers for the Suruí, an indigenous horticultural population in Brazil. We show that co-fathers roughly assort into two separate categories. In the affiliative category, co-father relationships are amicable when they are between close kin, namely brothers and father-son. In the competitive category, relationships are more likely of avoidance or open hostility when between more distant kin such as cousins or unrelated men of different clans. Results therefore imply multiple types of relationships, including both cooperative and competitive contexts, under the rubric of partible paternity. These complexities of partible paternity institutions add to our knowledge of the full range of cross-cultural variation in human mating/marriage arrangements and speak to the debate on whether or not humans should be classified as cooperative breeders.

Query‐centric scientific topic evolution extraction

ABSTRACTResearchers in academia and industry face a deluge of data in our digital world. In this paper, we investigate a novel problem, query‐centric scientific topic evolution. Using heterogeneous graph mining techniques we construct a topic evolution tree (TET) from massive collections of scientific publications, enabling students and researchers to explore the foundation of research topics outside their specialization. Prior research has focused mainly on citation relationships; in this study we employed multiple types of relationships, including authorship, citation, publishing venue, and the contributions authors, papers, and venues have made to a specific topic. We examine multiple restricted meta‐paths in constructing a TET covering topics from the MeSH vocabulary for biomedical research.

Multilayer networks

In most natural and engineered systems, a set of entities interact with each other in complicated patterns that can encompass multiple types of relationships, change in time and include other types of complications. Such systems include multiple subsystems and layers of connectivity, and it is important to take such ‘multilayer’ features into account to try to improve our understanding of complex systems. Consequently, it is necessary to generalize ‘traditional’ network theory by developing (and validating) a framework and associated tools to study multilayer systems in a comprehensive fashion. The origins of such efforts date back several decades and arose in multiple disciplines, and now the study of multilayer networks has become one of the most important directions in network science. In this paper, we discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. To unify the disparate terminology in the large body of recent work, we discuss a general framework for multilayer networks, construct a dictionary of terminology to relate the numerous existing concepts to each other and provide a thorough discussion that compares, contrasts and translates between related notions such as multilayer networks, multiplex networks, interdependent networks, networks of networks and many others. We also survey and discuss existing data sets that can be represented as multilayer networks. We review attempts to generalize single-layer-network diagnostics to multilayer networks. We also discuss the rapidly expanding research on multilayer-network models and notions like community structure, connected components, tensor decompositions and various types of dynamical processes on multilayer networks. We conclude with a summary and an outlook.

Coming Out and Fitting In: Same-Sex Marriage and the Politics of Difference

This article argues in favour of same-sex marriage, but only under certain conditions. Same-sex marriage ought to be introduced in the Australian context in order to remedy the formal inequalities between lesbian, gay, bisexual and transgender (LGBT) citizens and their heterosexual/cisgendered counterparts. One common method of justifying the introduction of formal same-sex relationship recognition has been via the promotion of LGBT "normalcy." This article explores such a trend by analysing popular media and advertising, since media representations and coverage have been shown to affect the way the general public "learns, understands, and thinks about an issue" (Li and Lui 73). This article finds that the promotion of normalcy can, in fact, perpetuate hetero-norms, and only offer LGBT people an imaginary social equality. Such normalisation, it is suggested, is detrimental to a wider goal of gaining respect for LGBT people regardless, not in spite of, their identity and relationships. Yet, this article maintains that such imaginary equality can be avoided, so long as a plurality of possibilities for one’s intimate and familial life are actively legitimated and promoted.

Probabilistic latent tensor factorization model for link pattern prediction in multi-relational networks

We address the problem of link prediction in collections of objects connected by multiple relation types, where each type may play a distinct role. While traditional link prediction models are limited to single-type link prediction we attempt here to jointly model and predict the multiple relation types, which we refer to as the link pattern prediction (LPP) problem. For that, we propose a probabilistic latent tensor factorization (PLTF) model and furnish the Bayesian treatment of the probabilistic model to avoid overfitting problem. To learn the proposed model we develop an efficient Markov chain Monte Carlo (MCMC) sampling method. Extensive experiments on several real world multi-relational datasets demonstrate the significant improvements of our model over several state-of-the-art methods.

Biomine: predicting links between biological entities using network models of heterogeneous databases

BackgroundBiological databases contain large amounts of data concerning the functions and associations of genes and proteins. Integration of data from several such databases into a single repository can aid the discovery of previously unknown connections spanning multiple types of relationships and databases.ResultsBiomine is a system that integrates cross-references from several biological databases into a graph model with multiple types of edges, such as protein interactions, gene-disease associations and gene ontology annotations. Edges are weighted based on their type, reliability, and informativeness. We present Biomine and evaluate its performance in link prediction, where the goal is to predict pairs of nodes that will be connected in the future, based on current data. In particular, we formulate protein interaction prediction and disease gene prioritization tasks as instances of link prediction. The predictions are based on a proximity measure computed on the integrated graph. We consider and experiment with several such measures, and perform a parameter optimization procedure where different edge types are weighted to optimize link prediction accuracy. We also propose a novel method for disease-gene prioritization, defined as finding a subset of candidate genes that cluster together in the graph. We experimentally evaluate Biomine by predicting future annotations in the source databases and prioritizing lists of putative disease genes.ConclusionsThe experimental results show that Biomine has strong potential for predicting links when a set of selected candidate links is available. The predictions obtained using the entire Biomine dataset are shown to clearly outperform ones obtained using any single source of data alone, when different types of links are suitably weighted. In the gene prioritization task, an established reference set of disease-associated genes is useful, but the results show that under favorable conditions, Biomine can also perform well when no such information is available.The Biomine system is a proof of concept. Its current version contains 1.1 million entities and 8.1 million relations between them, with focus on human genetics. Some of its functionalities are available in a public query interface at http://biomine.cs.helsinki.fi, allowing searching for and visualizing connections between given biological entities.

Personal relationships and innovation diffusion in SME networks: A content analysis approach

Networks have been hailed as a third organizational form, between markets and hierarchies. One of the main characteristics of networks is the coexistence of different kinds of relationships, personal and professional among these. The presence of multiple types of relationships modifies inter-firm dynamics, creating a space where traditional innovation activities take place in an unusual way. The present paper investigates the role played by personal relationships within networks, addressing the following research questions: how do different types of relationships existing in a network of SMEs favour the development of economic activities? And do personal relationships play a role in supporting innovative activities? To answer our research questions, we analyzed qualitative data using content analysis methodology. Content analysis allows researchers to obtain an objective, systematic, and quantitative description of the manifest content of a communication. Based on this analysis, we conclude that the coexistence of personal and professional relationships shapes a unique context that alters the usual dynamics of innovation diffusion.

The utility of the relationship assessment scale in multiple types of relationships

Several self-report scales of marital satisfaction exist, but many are too lengthy for research protocols, and none allow for parallel assessment of satisfaction in non-romantic relationships. This paper presents results from the assessment of satisfaction in multiple types of close relationships with slight adaptations to the wording of the seven-item Relationship Assessment Scale. This scale was tested in a series of four research protocols with over 1000 undergraduate students. The scale demonstrated good internal consistency, item reliabilities, test—retest reliability, and factorial validity across diverse types of close relationships, with preliminary evidence supporting its convergent and predictive validity as well. These results suggest that the Relationship Assessment Scale can briefly and adequately assess satisfaction in multiple types of relationships.

BSQA: integrated text mining using entity relation semantics extracted from biological literature of insects

Text mining is one promising way of extracting information automatically from the vast biological literature. To maximize its potential, the knowledge encoded in the text should be translated to some semantic representation such as entities and relations, which could be analyzed by machines. But large-scale practical systems for this purpose are rare. We present BeeSpace question/answering (BSQA) system that performs integrated text mining for insect biology, covering diverse aspects from molecular interactions of genes to insect behavior. BSQA recognizes a number of entities and relations in Medline documents about the model insect, Drosophila melanogaster. For any text query, BSQA exploits entity annotation of retrieved documents to identify important concepts in different categories. By utilizing the extracted relations, BSQA is also able to answer many biologically motivated questions, from simple ones such as, which anatomical part is a gene expressed in, to more complex ones involving multiple types of relations. BSQA is freely available at http://www.beespace.uiuc.edu/QuestionAnswer.

Such naches

This analysis of the papers in the special section on the intersection of identity development and peer relationship processes calls attention to conceptual contribution this collection of papers makes to the literature on identity development. Together these ten papers build on strong theoretical foundations in identity development, which posit close relationship contexts as central to the development of self-awareness and self-representation. The complex and innovative methodologies employed across these studies allow for the analysis of intersecting and interacting influence of multiple relationship types, and facilitate the analysis of culture and gender as they relate to identity development and peer processes. Together, these papers make a powerful contribution to the current literature and provide a foundation for future research.

Comparing parentage inference software: reanalysis of a red deer pedigree

Knowledge of the parentage of individuals is required to address a variety of questions concerning the evolutionary dynamics of wild populations. A major advance in parentage inference in natural populations has been the use of molecular markers and the development of statistical methods to analyse these data. Cervus, one of the most widely used parentage inference programs, uses molecular data to determine parent-offspring relationships. However, Cervus does not make use of all available information: additional phenotypic information may exist predicting parent-offspring relationships, and additional genetic information may be exploited by simultaneously considering multiple types of relationships rather than just pairwise or just parent-offspring relationships. Here we reanalyse data from a wild red deer population using two programs capable of using this additional information, MasterBayes and COLONY2, and quantify the impact of these alternative approaches by comparison with a 'known pedigree' estimated using a larger suite of microsatellite makers for a subset of the population. The use of phenotypic information and multiple relationships increased the number of correct assignments. We highlight the differences between programs, particularly the use of population- rather than individual-level statistical confidence in Cervus. We conclude that the use of additional information allows MasterBayes and COLONY2 to assign more correct paternities, whereas their use of individual- rather than population-level confidence generates fewer erroneous assignments. We suggest that maximal information may be gained by combining outputs from different programs. Higher accuracy and completeness of pedigree information will improve parameters estimated from pedigree information in studies of natural populations.

Trajectories of Peer Victimization: The Role of Multiple Relationships.

This study examined early elementary school children's trajectories of peer victimization with a sample of 218 boys and girls. Peer victimization was assessed (via peer report) in kindergarten, 1(st), 2(nd), and 5(th) grades. Hierarchical linear modeling (HLM) was used to examine multiple types of relationships (mother-child, student-teacher, friendship) as predictors of kindergarten levels of peer victimization and changes in peer victimization across time. Results indicated that the mother-child relationship predicted kindergarten levels of peer victimization, and that the student-teacher relationship did not provide additional information, once the mother-child relationship was accounted for in the analyses. Friendship predicted changes in peer victimization during the elementary school years. Results are discussed in a developmental psychopathology framework with special emphasis on the implication for understanding the etiology of peer victimization.

MizBee: A Multiscale Synteny Browser

In the field of comparative genomics, scientists seek to answer questions about evolution and genomic function by comparing the genomes of species to find regions of shared sequences. Conserved syntenic blocks are an important biological data abstraction for indicating regions of shared sequences. The goal of this work is to show multiple types of relationships at multiple scales in a way that is visually comprehensible in accordance with known perceptual principles. We present a task analysis for this domain where the fundamental questions asked by biologists can be understood by a characterization of relationships into the four types of proximity/location, size, orientation, and similarity/strength, and the four scales of genome, chromosome, block, and genomic feature. We also propose a new taxonomy of the design space for visually encoding conservation data. We present MizBee, a multiscale synteny browser with the unique property of providing interactive side-by-side views of the data across the range of scales supporting exploration of all of these relationship types. We conclude with case studies from two biologists who used MizBee to augment their previous automatic analysis work flow, providing anecdotal evidence about the efficacy oft he system for the visualization of syntenic data, the analysis of conservation relationships, and the communication of scientific insights.

When, Where, Why and with Whom Homeless Women Engage in Risky Sexual Behaviors: A Framework for Understanding Complex and Varied Decision-Making Processes

Impoverished women worldwide are at high risk for contracting HIV/AIDS. This study explores how homeless women make risky sex decisions and the role that alcohol and drugs play in this process. We analyze 56 in-depth qualitative descriptions of recent sexual episodes among 28 women living in shelters in Los Angeles, California, USA. The sample (age 18-63) was 46% African American, 21% Hispanic/Latina, and 21% white. Findings suggest that: (1) homeless women engage in multiple types of relationships and sexual behaviors; (2) emotion and attachment play critical roles in women's risky sex choices; and (3) the role of alcohol and drugs on such choices varies across relationship commitment. Understanding the complexity of sexual decision-making among this population has implications for developing successful risk reduction interventions.

Transforming the Culture of Biomedical Research From Compliance to Trustworthiness: Insights From Nonmedical Sectors

To discover ways that the biomedical research community can foster the public's trust essential to sustain the research enterprise, in 2005 the authors and their colleagues convened a group of national leaders from sectors outside of academic science and health care that are also dependent on the public's trust. These leaders provided information about what their sectors do to earn the public's trust that is applicable to academic biomedical research institutions, as well as insights into ways academic research institutions should respond to crises that have the potential to diminish the public's trust. The major strategies they identified for promoting the public's trust were the importance of fostering multiple types of relationships and developing accountability practices that exceed those required by external regulators.In this article, the authors compare these strategies with reports in the literature regarding efforts under way in health care to adapt strategies employed in other sectors to improve the safety of health care. On the basis of what the authors learned from both the national leaders outside of biomedical research and health care and the health care safety literature review, they present a set of recommendations for building and restoring trust, as well as a list of benchmarks for assessing the adequacy of efforts by research institutions to promote the public's trust in biomedical research.

Implementing E-Justice on a National Scale

The world of justice is undergoing drastic changes that commenced about a decade ago. Trends in an effort for enterprise like management, along with the advent of information and communication technologies, have culminated in a strong imperative for technological and organizational reforms. However, justice is not simply another sector for e-government implementations. Justice is an autonomous function of democratic regimes that not only interprets laws but also poses restrictions and preconditions on how electronic systems are implemented with concern for the protection of constitutional and civil rights. Multiple types of relationships have been developed between politicians, administrators, technological infrastructure providers, and businesses, converting the roadmap for e-justice implementation from a mere quantified investment on content and organization to a complex strategy involving broader social and economical modeling techniques. Using case studies in three Balkan countries this research illustrates the problems in applying e-justice on a national scale.

Introduction to the special issue on link mining

An emerging challenge for data mining is the problem of mining richly structured datasets, where the objects are linked in some way. Many real-world datasets describe a variety of entity types linked via multiple types of relations. These links provide additional context that can be helpful for many data mining tasks. Yet multi-relational data violates the traditional assumption of independent, identically distributed data instances that provides the basis for many statistical machine learning algorithms. Therefore, new approaches are needed that can exploit the dependencies across the attribute and link structure.

Crossover sexual offenses.

Crossover sexual offenses are defined as those in which victims are from multiple age, gender, and relationship categories. This study investigates admissions of crossover sexual offending from sex offenders participating in treatment who received polygraph testing. For 223 incarcerated and 266 paroled sexual offenders, sexual offenses were recorded from criminal history records and admissions during treatment coupled with polygraph testing. The majority of incarcerated offenders admitted to sexually assaulting both children and adults from multiple relationship types. In addition, there was a substantial increase in offenders admitting to sexually assaulting victims from both genders. In a group of incarcerated offenders who sexually assaulted children, the majority of offenders admitted to sexually assaulting both relatives and nonrelatives, and there was a substantial increase in the offenders admitting to assaulting both male and female children. Although similar trends were observed for the sample of parolees, the rates were far less dramatic. Parolees appeared to have greater levels of denial, had participated in fewer treatment sessions, and perceived greater supervision restrictions as a result of admitting additional offenses. These findings support previous research indicating that many sexual offenders do not exclusively offend against a preferred victim type.