Towards Building a Knowledge Base of Monetary Transactions from a News Collection

We address the problem of extracting structured representations of economic events from a large corpus of news articles, using a combination of natural language processing and machine learning techniques. The developed techniques allow for semi-automatic population of a financial knowledge base, which, in turn, may be used to support a range of data mining and exploration tasks. The key challenge we face in this domain is that the same event is often reported multiple times, with varying correctness of details. We address this challenge by first collecting all information pertinent to a given event from the entire corpus, then considering all possible representations of the event, and finally, using a supervised learning method, to rank these representations by the associated confidence scores. A main innovative element of our approach is that it jointly extracts and stores all attributes of the event as a single representation (quintuple). Using a purpose-built test set we demonstrate that our supervised learning approach can achieve 25% improvement in F1-score over baseline methods that consider the earliest, the latest or the most frequent reporting of the event.Comment: Proceedings of the 17th ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL '17), 201

Temporal Expertise Profiling

Abstract. We introduce the temporal expertise profiling task: identifying the skills and knowledge of an individual and tracking how they change over time. To be able to capture and distinguish meaningful changes, we propose the concept of a hierarchical expertise profile, where topical areas are organized in a taxonomy. Snapshots of hierarchical profiles are then taken at regular time intervals. Further, we develop methods for detecting and characterizing changes in a person’s profile, such as, switching the main field of research or narrowing/broadening the topics of research. Initial results demonstrate the potential of our approach.

Report on the 44th European Conference on Information Retrieval (ECIR 2022): The First Major Hybrid IR Conference

The 44th European Conference on Information Retrieval (ECIR’22) was held in Stavanger, Norway. It represents a landmark, not only for being the northernmost ECIR ever, but also for being the first major IR conference in a hybrid format. This article reports on ECIR’22 from the organizers’ perspective, with a particular emphasis on elements of the hybrid setup, with the aim to serve as a reference and guidance for future hybrid conferences.publishedVersio

Har sosial kapital betydning for global livskvalitet i Østfold? : en tverrsnittstudie av befolkningen i Østfold 2019

Bakgrunn: Livskvalitet er et viktig mål på hvordan det står til i befolkningen og er dermed viktig for folkehelsearbeidet. Norge ligger i verdenstoppen når det kommer til livskvalitet, men nivået har gradvis sunket de siste årene. En av faktorene som har blitt vist å ha en innvirkning på livskvalitet er sosial kapital. I tillegg kan sosiodemografiske faktorer virke inn. Men det er lite forskning i Norge på disse sammenhengene, og det er behov for ytterligere kunnskap i en norsk kontekst. Hensikt: Å undersøke sammenhengen mellom sosial kapital og global livskvalitet, og se hvordan sosiodemografiske variabler påvirker denne sammenhengen. Metode: Denne tverrsnittstudien hadde et analytisk utvalg på 12 815 personer (18-79 år). Datamaterialet som ble benyttet ble hentet fra Oss i Østfold 2019, en nettbasert befolkningsundersøkelse om levekår, helse og livskvalitet i Østfold fylkeskommune. Det ble benyttet logistisk regresjonsanalyse for å undersøke sammenhengen mellom sosial kapital (tillit, sosial støtte, deltakelse og tilhørighet), sosiodemografiske variabler og global livskvalitet. I analysen ble det også kontrollert for ensomhet, fysisk aktivitet og langvarig sykdom eller helseproblem. Resultater: Gjennomsnittet for global livskvalitet i Østfold lå på 7.5 på en skala fra 0- 10. Resultatene viste at høy grad av tillit, sosial støtte, deltakelse og tilhørighet ga en økt odds for å rapportere høy global livskvalitet. Oddsen for å rapportere høy global livskvalitet var også høyere for kvinner, med økende alder, for de med partner, sysselsatte, pensjonister og de som opplevde sin økonomiske situasjon som lett. Den fulljusterte regresjonsmodellen forklarte 42 % av variansen i global livskvalitet. Konklusjon: Denne studien viser at det er viktig at det legges til rette for økt sosial kapital og redusert ulikhet i folkehelsearbeidet for å bedre befolkningens globale livskvalitet.Background: Well-being is an important measurement of how the population is doing and is thus important for public health. Norway ranks among the top internationally on the level of well-being, however the level has declined in recent years. One of the factors that has been shown to have an impact on well-being is social capital. In addition, socio-demographic factors have also been shown to have an impact. There is still a need for further knowledge about how social capital and socio-demographic factors affect well-being in a Norwegian context. Aim: To investigate the association between social capital and global well-being, and how socio-demographic variables affect the association. Methods: This cross-sectional study had an analytical sample of 12,815 (18 to 79 years). The data material used was taken from «Oss i Østfold 2019», an online population survey on living conditions, health and well-being in Østfold County Municipality. Logistic regression analysis was used to examine the relationship between social capital (trust, social support, participation and belonging), socio-demographic variables and global well-being. The model was controlled for loneliness, physical activity, and long-term illness or health problems. Results: The average for global well-being in Østfold was 7.5 on a scale from 0-10. The results showed that a high degree of trust, social support, participation and belonging increased the odds of reporting high global well-being. The odds of reporting a high global well-being were also higher for women, with increasing age, for those with a partner, employees, pensioners, and those who experienced their financial situation as easy. The fully adjusted regression model explained 42% of the variance in global well-being. Conclusion: The study shows that it is important to facilitate increased social capital and reduce inequality in public health in order to improve the population's global well-being.M-FO

Exploring Decomposition for Solving Pattern Mining Problems

This article introduces a highly efficient pattern mining technique called Clustering-based Pattern Mining (CBPM). This technique discovers relevant patterns by studying the correlation between transactions in the transaction database based on clustering techniques. The set of transactions is first clustered, such that highly correlated transactions are grouped together. Next, we derive the relevant patterns by applying a pattern mining algorithm to each cluster. We present two different pattern mining algorithms, one applying an approximation-based strategy and another based on an exact strategy. The approximation-based strategy takes into account only the clusters, whereas the exact strategy takes into account both clusters and shared items between clusters. To boost the performance of the CBPM, a GPU-based implementation is investigated. To evaluate the CBPM framework, we perform extensive experiments on several pattern mining problems. The results from the experimental evaluation show that the CBPM provides a reduction in both the runtime and memory usage. Also, CBPM based on the approximate strategy provides good accuracy, demonstrating its effectiveness and feasibility. Our GPU implementation achieves significant speedup of up to 552× on a single GPU using big transaction databases.publishedVersio