Unsupervised Keyword Extraction from Polish Legal Texts

In this work, we present an application of the recently proposed unsupervised keyword extraction algorithm RAKE to a corpus of Polish legal texts from the field of public procurement. RAKE is essentially a language and domain independent method. Its only language-specific input is a stoplist containing a set of non-content words. The performance of the method heavily depends on the choice of such a stoplist, which should be domain adopted. Therefore, we complement RAKE algorithm with an automatic approach to selecting non-content words, which is based on the statistical properties of term distribution

Complaint Analysis in Indonesian Language Using WPKE and RAKE Algorithm

Social media provides convenience in communicating and can present two-way communication that allows companies to interact with their customer. Companies can use information obtained from social media to analyze how the communities respond to their services or products. The biggest challenge in processing information in social media like Twitter, is the unstructured sentences which could lead to incorrect text processing. However, this information is very important for companies’ survival. In this research, we proposed a method to extract keywords from tweets in Indonesian language, WPKE. We compared it with RAKE, an algorithm that is language independent and usually used for keyword extraction. Finally, we develop a method to do clustering to groups the topics of complaints with data set obtained from Twitter using the “komplain” hashtag. Our method can obtain the accuracy of 72.92% while RAKE can only obtain 35.42%

Stopword Dinamis Dengan Pendekatan Statistik

Stopword merupakan sebagian kecil kata yang sering muncil pada setiap dokumen korpus. Kata-kata tersebut tidak memberikan makna berarti pada dokumen, sehingga kemunculan kata-kata tersebut dalam indek membuat hasil temu kembali menjadi tidak akurat. Daftar stopword atau biasa disebut dengan stoplist menjadi bagian terpenting dalam proses filtering menghilangkan stopword dari indek temu kembali informasi. Stoplist bisa di dapatkan dari kamus bahasa atau dari beberapa referensi penelitian temu kembali yang menghasilkan daftar stopword [1]. Stopword sangat tergantung dengan bahasa yang digunakan di korpus, sehingga bahasa yang disediakan oleh stoplist harus sama dengan bahasa yang digunakan di korpus. Korpus yang terdiri dari bermacam-macam bahasa tidak bisa mengandalkan stoplist statis seperti pada penelitian tala, Terlebih apabila korpus tersebut berkembang menjadi lebih dari satu bahasa dan atau domain [2]. Demikian pula pada korpus-korpus pada domain yang lebih spesifik beberapa kata yang bukan stopword pada korpus kebanyakan bisa jadi menjadi stopword pada suatu domain korpus. Sebagai contoh kata "resep" akan menjadi stopword pada korpus dengan domain resep masakan

Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation

Peer reviewe

Text mining and natural language processing for the early stages of space mission design

Final thesis submitted December 2021 - degree awarded in 2022A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes.A considerable amount of data related to space mission design has been accumulated since artificial satellites started to venture into space in the 1950s. This data has today become an overwhelming volume of information, triggering a significant knowledge reuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants, text mining and Natural Language Processing techniques have become pervasive to our daily life. The work presented in this thesis is one of the first attempts to bridge the gap between the worlds of space systems engineering and text mining. Several novel models are thus developed and implemented here, targeting the structuring of accumulated data through an ontology, but also tasks commonly performed by systems engineers such as requirement management and heritage analysis. A first collection of documents related to space systems is gathered for the training of these methods. Eventually, this work aims to pave the way towards the development of a Design Engineering Assistant (DEA) for the early stages of space mission design. It is also hoped that this work will actively contribute to the integration of text mining and Natural Language Processing methods in the field of space mission design, enhancing current design processes

Unlocking environmental narratives: towards understanding human environment interactions through computational text analysis

Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities

Unlocking Environmental Narratives

Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities