| 1. |
- Alfalahi, Alyaa, et al.
(författare)
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Expanding a dictionary of marker words for uncertainty and negation using distributional semantics
- 2015
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Ingår i: EMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 : Proceedings of the Workshop - Proceedings of the Workshop. - : Association for Computational Linguistics. - 9781941643327 ; , s. 90-96
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Konferensbidrag (refereegranskat)abstract
- Approaches to determining the factuality of diagnoses and findings in clinical text tend to rely on dictionaries of marker words for uncertainty and negation. Here, a method for semi-automatically expanding a dictionary of marker words using distributional semantics is presented and evaluated. It is shown that ranking candidates for inclusion according to their proximity to cluster centroids of semantically similar seed words is more successful than ranking them according to proximity to each individual seed word.
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| 2. |
- Alfalahi, Alyaa, et al.
(författare)
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Pseudonymisation of Personal Names and other PHIs in an Annotated Clinical Swedish Corpus
- 2012
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Ingår i: LREC 2012, Eighth International Conference on Language Resources and Evaluation. - 9782951740877
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Konferensbidrag (refereegranskat)abstract
- Today a large number of patient records are produced and these records contain valuable information, often in free text, about the medical treatment of patients. Since these records contain information that can reveal the identity of patients, known as protected health information (PHI), the records cannot easily be made available for the research community. In this research we have used a PHI annotated clinical corpora, written in Swedish, that we have pseudonymised. Pseudonymisation means to replace the sensitive information with fictive information for example real personal names are replaced with fictive personal names based on the gender of the real names and family relations. We have evaluated our results and our five respondents of who three were clinicians found that the clinical text looks real and is readable. We have also added pseudonymisation for telephone numbers, locations, health care units, dates and ages. In this paper we also present the entire de-identification and pseudonymisation process of a sample clinical text.
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| 3. |
- Alfalahi, Alyaa, et al.
(författare)
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Shadow Answers as an Intermediary in Email Answer Retrieval
- 2015
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Ingår i: Experimental IR Meets Multilinguality, Multimodality, and Interaction. - Cham : Springer. - 9783319240268 - 9783319240275 ; , s. 209-214
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Konferensbidrag (refereegranskat)abstract
- A set of standard answers facilitates answering emails at customer care centers. Matching the text of user emails to the standard answers may not be productive because they do not necessarily have the same wording. Therefore we examine archived email-answer pairs and establish query-answer term co-occurrences. When a new user email arrives, we replace query words with most co-occurring answer words and obtain a “shadow answer”, which is a new query to retrieve standard answers. As a measure of term co-occurrence strength we test raw term co-occurrences and Pointwise Mutual Information.
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| 4. |
- Knutsson, Ola, et al.
(författare)
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Opportunities for Improving eGovernment : Using Language Technology in Workflow Management
- 2012
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Ingår i: ICEGOV 2012. The 6 th International Conference on Theory and Practice of Electronic Governance. - : ACM Press. - 9781450312004 ; , s. 495-496
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Konferensbidrag (refereegranskat)abstract
- Workflow management deals with a fair amount of free text – scanned paper documents, web input forms, e-mail, input from mobile devices as well as texts from government agencies to citizens. The free-text input is intended for a human reader. Still, in eGovernment settings we would like to process such input before, while and after handling officers read it. This paper presents some examples on how language technology can increase efficiency and quality of workflow management.
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| 5. |
- Sneiders, Eriks, et al.
(författare)
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Automated email answering by text-pattern matching : Performance and error analysis
- 2018
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Ingår i: Expert systems (Print). - : Wiley. - 0266-4720 .- 1468-0394. ; 35:1
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Tidskriftsartikel (refereegranskat)abstract
- Automated answering of frequent email inquiries can be implemented as a text categorization task with narrow text categories, where all messages in 1 text category have the same answer. Such email categorization should be optimized for high precision and at least acceptable recall. One such high-precision email categorization method is matching of surface text patterns to incoming email messages. In order to assess the upper performance limits of text-pattern matching, we conducted extensive tests with almost 10,000 messages. Our results show that automated email answering with precision around 90% and recall 50–75% is feasible. In order to achieve this, however, the system must work with multiword expressions rather than stand-alone words. Furthermore, we argue that the system has to distinguish the context of an email inquiry from the actual need that created the inquiry—a question, request, or complaint. We have discovered and analysed 12 reasons why text-pattern matching may fail.
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| 6. |
- Sneiders, Eriks, et al.
(författare)
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Email Answering by Matching Question and Context-Specific Text Patterns : Performance and Error Analysis
- 2016
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Ingår i: New Advances in Information Systems and Technologies. - Cham : Springer. - 9783319312316 - 9783319312323 ; , s. 123-133
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Konferensbidrag (refereegranskat)abstract
- Automated answering of frequent email inquiries is a text categorization task with narrow text categories, where all messages in one text category have the same answer. Such email categorization is optimized for high precision and at least acceptable recall. We tested matching of surface text patterns to nearly ten thousand email messages and achieved around 90% precision; the corresponding recall figures were 45-75% in different text categories. In order to achieve this performance level, the text patterns are designed to identify both the context of an email inquiry and the actual need that has created the inquiry – a question, request, or complaint. Our error analysis has pinpointed 12 reasons why text pattern matching may fail.
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| 7. |
- Sneiders, Eriks, et al.
(författare)
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Exploring the Traits of Manual E-Mail Categorization Text Patterns
- 2014
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Ingår i: Advances in Natural Language Processing. - Cham : Springer. - 9783319108872 - 9783319108889 ; , s. 337-344
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Konferensbidrag (refereegranskat)abstract
- Automated e-mail answering with a standard answer is a text categorization task. Text categorization by matching manual text patterns to messages yields good performance if the text categories are specific. Given that manual text patterns embody informal human perception of important wording in a written inquiry, it is interesting to investigate more formal traits of this important wording, such as the amount of matching text, distance between matching words, n-grams, part-of-speech patterns, and vocabulary in the matching words. Understanding these features may help us better design text-pattern extraction algorithms.
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