Information extraction from procurement contracts

The increasing amount of text data produced by companies demands automating the extraction of key information from contracts. It removes the manual step of inserting contract metadata into contract management software. This improves the efficiency and meaningfulness of work for procurement professionals as they will have growing amount of time in more creative and value-creating tasks. Previous information extraction research has considered many fields but left a gap in complete procurement contract documents. This study aimed to contribute to filling that gap by experimenting methods of extracting contract metadata from multi-paged non-standard documents. The best methods for extracting contracting parties, effective dates, payment terms, liabilities, and contracting periods were investigated. The automation can be done utilizing methods of natural language processing. A tool for automatic extraction was created applying named-entity recognition algorithms and hand-crafted rules. Quantitative results were obtained from the tool. These results were discussed in semi-structured interviews with professionals from the case company Sievo Oy. A key finding of this study was that the combination of methods used in the extraction performs well with contracting parties, while with other items more work needs to be done. Despite the varying results from the extraction, the interviews exposed an alternative way of easing the work of finding key information from contracts. It was suggested that instead of completely automating the task, the software could act as an assistant for its users. How this possibility is utilized and what is the reception of the users remains to be seen.Yritykset tuottavat kasvavassa määrin tekstidataa. Tähän kehitykseen vastaamaan tarvitaan automaattista avaintietojen eristämistä sopimustiedostoista. Automatisointi poistaa aikaa vievän työvaiheen, jossa sopimuksen metatietoja syötetään käsin sopimustenhallintajärjestelmiin. Tällä tavoin voidaan parantaa hankintatoimen tehokkuutta ja työntekijöiden kokemaa työn merkityksellisyyttä, kun työaikaa voidaan käyttää luoviin ja arvoa tuottaviin tehtäviin. Aiemmassa tiedon eristämistä koskevassa tutkimuksessa on käsitelty monenlaisia tekstityyppejä, mutta kokonaiset hankintasopimukset ovat jääneet vaille huomiota. Tämän tutkimuksen tarkoituksena oli olla täyttämässä tätä aukkoa etsimällä menetelmiä, joilla voidaan eristää metatietoja monisivuisista epästandardeista sopimuksista. Parhaiksi todettuja menetelmiä tiedon eristämiseen sovellettiin sopijaosapuoliin, voimaantulopäivään, maksuehtoihin, vastuisiin ja sopimuksen kestoon. Automaatiossa hyödynnettiin luonnollisen kielen käsittelyn menetelmiä. Kehitetyssä ohjelmassa käytettiin nimentunnistuksen algoritmeja ja käsin määriteltyjä sääntöjä. Ohjelma tuotti määrällisiä tuloksia, joista keskusteltiin case-yritys Sievo Oy:n asiantuntijoiden kanssa puolistrukturoiduissa haastatteluissa. Tutkimuksen keskeisten löydösten pohjalta sopivaksi valikoitunut menetelmien yhdistelmä toimi hyvin sopijaosapuolten kohdalla. Muiden eristettävien nimikkeiden kohdalla työtä on vielä edessä. Vaihtelevista tuloksista huolimatta haastatteluissa keskeiseksi teemaksi nousi vaihtoehtoinen toimintatapa, joka helpottaisi avaintietojen eristämistä sopimuksista. Haastateltavat nostivat esiin mahdollisuuden käyttää ohjelmistoa avustajana täyden automatisoinnin sijaan. Nähtäväksi jää, miten tätä mahdollisuutta hyödynnetään, ja millaisen vastaanoton se saa käyttäjiltä

Fall 2017

https://scholar.rose-hulman.edu/rose_echoes/1096/thumbnail.jp

The Palgrave Handbook of Digital Russia Studies

This open access handbook presents a multidisciplinary and multifaceted perspective on how the ‘digital’ is simultaneously changing Russia and the research methods scholars use to study Russia. It provides a critical update on how Russian society, politics, economy, and culture are reconfigured in the context of ubiquitous connectivity and accounts for the political and societal responses to digitalization. In addition, it answers practical and methodological questions in handling Russian data and a wide array of digital methods. The volume makes a timely intervention in our understanding of the changing field of Russian Studies and is an essential guide for scholars, advanced undergraduate and graduate students studying Russia today

Data and the city – accessibility and openness. a cybersalon paper on open data

This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data

The Palgrave Handbook of Digital Russia Studies

This open access handbook presents a multidisciplinary and multifaceted perspective on how the ‘digital’ is simultaneously changing Russia and the research methods scholars use to study Russia. It provides a critical update on how Russian society, politics, economy, and culture are reconfigured in the context of ubiquitous connectivity and accounts for the political and societal responses to digitalization. In addition, it answers practical and methodological questions in handling Russian data and a wide array of digital methods. The volume makes a timely intervention in our understanding of the changing field of Russian Studies and is an essential guide for scholars, advanced undergraduate and graduate students studying Russia today

The Molecular and Cellular Basis of Retinal Diseases

There are more than 300 genes that have been identified which carry mutations that cause various forms of retinal dysfunction and degeneration, making the study of retinal diseases a subject of high relevance. In this compendium of original and review articles, many of the diseases and pathways associated with disorders of the retina are examined using animal models, to provide the reader with a good overview of current retinal research. Within this volume, you will find research reports on many of the most prominent retinal disorders, such as diabetic retinopathy (DR), age-related macular degeneration (AMD), choroidal neovascularization (CNV), and retinitis pigmentosa (RP). We hope that the work presented here will stimulate new ideas and lead to effective treatments for retinal diseases

Ubiquitin and Autophagy

This book is a collection of articles from the Cells Special Issue on “Ubiquitin and Autophagy”. It contains an Editorial and 13 articles at the intersection of ubiquitin- and autophagy-related processes. Ubiquitin is a small protein modifier that is widely used to tag proteins, organelles, and pathogens for their degradation by the ubiquitin–proteasome system and/or autophagy–lysosomal pathway. Interestingly, several ubiquitin-like proteins are at a core of the autophagy mechanism. This book dedicates a lot of attention to the crosstalk between the ubiquitin–proteasome system and autophagy and serves as a good starting point for the readers interested in the current state of the knowledge on ubiquitin and autophagy

Neural Network Based OCR for Keg Identification

A keg asset management system that can reduce the annual rate of keg attrition by 5% to 20% can deliver significant savings to breweries with large fleets of kegs. A typically large brewery can have at least tens of thousands of kegs, a sizable investment given an initial cost of around USD100 per keg. A key element in a keg tracking system is on-line keg identification. This research explores the feasibility of an intelligent machine vision approach to identifying the unique serial number embossed on the dome of each keg at manufacture. The demonstration system developed auto-locates candidate serial numbers and applies optical character recognition (OCR) techniques. The neural network based OCR achieved the best performance over template matching achieving an overall recognition rate of 92% and no missed digits. If non-permanent serial number occlusions can be removed by caustic washing prior to the image capture stage in a production line implementation, the recognition rate approaches 97%