Besides finding trends and unveiling typical patterns, modern information retrieval is increasingly more interested in the discovery of surprising information in textual datasets. In this work we focus on finding "unexpected links" in hyperlinked document corpora when documents are assigned to categories. To achieve this goal, we model the hyperlinks graph through node categories: the presence of an arc is fostered or discouraged by the categories of the head and the tail of the arc. Specifically, we determine a latent category matrix that explains common links. The matrix is built using a margin-based online learning algorithm (Passive-Aggressive), which makes us able to process graphs with @math links in less than @math minutes. We show that our method provides better accuracy than most existing text-based techniques, with higher efficiency and relying on a much smaller amount of information. It also provides higher precision than standard link prediction, especially at low recall levels; the two methods are in fact shown to be orthogonal to each other and can therefore be fruitfully combined.
Interpreting links in a network as a result of features of each node has a solid empirical background. The simple phenomenon of homophily -- i.e, links between nodes sharing the same features -- has been widely studied in social networks @cite_25 and other complex systems @cite_4 . More complex behavior, where nodes with certain features tend to connect to another type of nodes, has also proven to be greatly beneficial in analyzing real social networks. Tendencies of such kind are called and are often described by a category-category matrix @cite_20 . For example, they appeared to be a crucial factor in tracking the spread of sexual diseases @cite_5 as well as in modelling the transmission of respiratory infections @cite_32 . For this reason, such matrices are also called Who Acquires Infection From Whom'' (WAIFW) matrices, and have been empirically assessed in the field through surveys @cite_22 and with wearable sensors @cite_33 .
@cite_4 @cite_22 @cite_33 @cite_32 @cite_5 @cite_25 @cite_20
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The fact that similarity breeds connections, the principle of homophily, has been well-studied in existing sociology literature. Several studies have observed this phenomenon by conducting surveys on human subjects. These studies have concluded that new ties are formed between similar individuals. This phenomenon has been used to explain several socio-psychological concepts such as, segregation, community development, social mobility, etc. However, due to the nature of these studies and limitations because of involvement of human subjects, conclusions from these studies are not easily extensible in online social media. Social media, which is becoming the infinite space for interactions, has exceeded all the expectations in terms of growth, for reasons beyond human mind. New ties are formed in social media in the same way that they emerge in real-world. However, given the differences between real world and online social media, do the same factors that govern the construction of new ties in real world also govern the construction of new ties in social media? In other words, does homophily exist in social media? In this article, we study this extremely significant question. We propose a systematic approach by studying three online social media sites, BlogCatalog, Last.fm, and LiveJournal and report our findings along with some interesting observations. The results indicate that the influence of interest-based homophily is not a very strong leading factor for constructing new ties specifically in the three social media sites with implications to strategic advertising, recommendations, and promoting applications at large. Background Until recently, mathematical models of person to person infectious diseases transmission had to make assumptions on transmissions enabled by personal contacts by estimating the so-called WAIFW-matrix. In order to better inform such estimates, a population based contact survey has been carried out in Belgium over the period March-May 2006. In contrast to other European surveys conducted simultaneously, each respondent recorded contacts over two days. Special attention was given to holiday periods, and respondents with large numbers of professional contacts. Background Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals. Methods and Findings We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25 of the contacts involved a ward assistant, 23 a nurse, 22 a patient, 22 a caregiver, and 8 a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections. Conclusions Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings. Background Mathematical modelling of infectious diseases transmitted by the respiratory or close-contact route (e.g., pandemic influenza) is increasingly being used to determine the impact of possible interventions. Although mixing patterns are known to be crucial determinants for model outcome, researchers often rely on a priori contact assumptions with little or no empirical basis. We conducted a population-based prospective survey of mixing patterns in eight European countries using a common paper-diary methodology. OBJECTIVES: This study sought to define, among sexually transmitted disease (STD) clinic attendees, (1) patterns of sex partner selection, (2) relative risks for gonococcal or chlamydial infection associated with each mixing pattern, and (3) selected links and potential and actual bridge populations. METHODS: Mixing matrices were computed based on characteristics of the study participants and their partners. Risk of infection was determined in study participants with various types of partners, and odds ratios were used to estimate relative risk of infection for discordant vs concordant partnerships. RESULTS: Partnerships discordant in terms of race ethnicity, age, education, and number of partners were associated with significant risk for gonorrhea and chlamydial infection. In low-prevalence subpopulations, within-subpopulation mixing was associated with chlamydial infection, and direct links with high-prevalence subpopulations were associated with gonorrhea. CONCLUSIONS: Mixing patterns influence the ris... Similarity breeds connection. This principle—the homophily principle—structures network ties of every type, including marriage, friendship, work, advice, support, information transfer, exchange, comembership, and other types of relationship. The result is that people's personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics. Homophily limits people's social worlds in a way that has powerful implications for the information they receive, the attitudes they form, and the interactions they experience. Homophily in race and ethnicity creates the strongest divides in our personal environments, with age, religion, education, occupation, and gender following in roughly that order. Geographic propinquity, families, organizations, and isomorphic positions in social systems all create contexts in which homophilous relations form. Ties between nonsimilar individuals also dissolve at a higher rate, which sets the stage for the formation of niches (localize...