Magnus Rosell


2018

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FOI DSS at SemEval-2018 Task 1: Combining LSTM States, Embeddings, and Lexical Features for Affect Analysis
Maja Karasalo | Mattias Nilsson | Magnus Rosell | Ulrika Wickenberg Bolin
Proceedings of The 12th International Workshop on Semantic Evaluation

This paper describes the system used and results obtained for team FOI DSS at SemEval-2018 Task 1: Affect In Tweets. The team participated in all English language subtasks, with a method utilizing transfer learning from LSTM nets trained on large sentiment datasets combined with embeddings and lexical features. For four out of five subtasks, the system performed in the range of 92-95% of the winning systems, in terms of the competition metrics. Analysis of the results suggests that improved pre-processing and addition of more lexical features may further elevate performance.

2010

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Text Cluster Trimming for Better Descriptions and Improved Quality
Magnus Rosell
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Text clustering is potentially very useful for exploration of text sets that are too large to study manually. The success of such a tool depends on whether the results can be explained to the user. An automatically extracted cluster description usually consists of a few words that are deemed representative for the cluster. It is preferably short in order to be easily grasped. However, text cluster content is often diverse. We introduce a trimming method that removes texts that do not contain any, or a few of the words in the cluster description. The result is clusters that match their descriptions better. In experiments on two quite different text sets we obtain significant improvements in both internal and external clustering quality for the trimmed clustering compared to the original. The trimming thus has two positive effects: it forces the clusters to agree with their descriptions (resulting in better descriptions) and improves the quality of the trimmed clusters.

2009

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Global Evaluation of Random Indexing through Swedish Word Clustering Compared to the People’s Dictionary of Synonyms
Magnus Rosell | Martin Hassel | Viggo Kann
Proceedings of the International Conference RANLP-2009

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Part of Speech Tagging for Text Clustering in Swedish
Magnus Rosell
Proceedings of the 17th Nordic Conference of Computational Linguistics (NODALIDA 2009)

2008

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Revealing Relations between Open and Closed Answers in Questionnaires through Text Clustering Evaluation
Magnus Rosell | Sumithra Velupillai
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

Open answers in questionnaires contain valuable information that is very time-consuming to analyze manually. We present a method for hypothesis generation from questionnaires based on text clustering. Text clustering is used interactively on the open answers, and the user can explore the cluster contents. The exploration is guided by automatic evaluation of the clusters against a closed answer regarded as a categorization. This simplifies the process of selecting interesting clusters. The user formulates a hypothesis from the relation between the cluster content and the closed answer categorization. We have applied our method on an open answer regarding occupation compared to a closed answer on smoking habits. With no prior knowledge of smoking habits in different occupation groups we have generated the hypothesis that farmers smoke less than the average. The hypothesis is supported by several separate surveys. Closed answers are easy to analyze automatically but are restricted and may miss valuable aspects. Open answers, on the other hand, fully capture the dynamics and diversity of possible outcomes. With our method the process of analyzing open answers becomes feasible.

2006

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Free construction of a free Swedish dictionary of synonyms
Viggo Kann | Magnus Rosell
Proceedings of the 15th Nordic Conference of Computational Linguistics (NODALIDA 2005)

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The impact of phrases in document clustering for Swedish
Magnus Rosell | Sumithra Velupillai
Proceedings of the 15th Nordic Conference of Computational Linguistics (NODALIDA 2005)