# TFW2V: An Enhanced Document Similarity Method for the Morphologically Rich Finnish Language

arXiv: https://arxiv.org/abs/2112.12489 · HTML: https://mlsanity.com/paper/2112.12489/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 38 references that are in the map.
- First posted on arXiv 23 Dec 2021.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter](https://mlsanity.com/paper/1910.01108/) (2019)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [HuggingFace's Transformers: State-of-the-art Natural Language Processing](https://mlsanity.com/paper/1910.03771/) (2019)
- [Distributed Representations of Sentences and Documents](https://mlsanity.com/paper/1405.4053/) (2014)
- [Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation](https://mlsanity.com/paper/2004.09813/) (2020)
- [Multilingual Universal Sentence Encoder for Semantic Retrieval](https://mlsanity.com/paper/1907.04307/) (2019)
- [Let's FACE it. Finnish Poetry Generation with Aesthetics and Framing](https://mlsanity.com/paper/1910.13946/) (2019)
- [An Unsupervised method for OCR Post-Correction and Spelling Normalisation for Finnish](https://mlsanity.com/paper/2011.03502/) (2020)
- [The Current State of Finnish NLP](https://mlsanity.com/paper/2109.11326/) (2021)
- [Cross-Discourse and Multilingual Exploration of Textual Corpora with the DualNeighbors Algorithm](https://mlsanity.com/paper/1806.11183/) (2018)
- [How Cute is Pikachu? Gathering and Ranking Pok'emon Properties from Data with Pok'emon Word Embeddings](https://mlsanity.com/paper/2108.09546/) (2021)

## Abstract (arXiv)

Measuring the semantic similarity of different texts has many important applications in Digital Humanities research such as information retrieval, document clustering and text summarization. The performance of different methods depends on the length of the text, the domain and the language. This study focuses on experimenting with some of the current approaches to Finnish, which is a morphologically rich language. At the same time, we propose a simple method, TFW2V, which shows high efficiency in handling both long text documents and limited amounts of data. Furthermore, we design an objective evaluation method which can be used as a framework for benchmarking text similarity approaches.