Informatica

In this paper, we propose a light-weight electronic voting protocol. The approach used by our protocol to conceal the ballots does not imply encryption, and guarantees the privacy of the direction of the vote unless all the contestants (parties) agree to do so. Our method is based on the division of the ballot into different pieces of information, which separately reveal no information at all, and that can be latter aggregated to recover the original vote. We show that, despite its simplicity, this scheme is powerful, it does not sacrifice any of the security properties demanded in a formal electronic voting protocol, and, furthermore, even in post-quantum scenarios, neither the casted votes can be tampered with, nor the identity of any elector can be linked with the direction of her vote.

This paper describes our research on statistical language modeling of Lithuanian. The idea of improving sparse n‐gram models of highly inflected Lithuanian language by interpolating them with complex n‐gram models based on word clustering and morphological word decomposition was investigated. Words, word base forms and part‐of‐speech tags were clustered into 50 to 5000 automatically generated classes. Multiple 3‐gram and 4‐gram class‐based language models were built and evaluated on Lithuanian text corpus, which contained 85 million words. Class‐based models linearly interpolated with the 3‐gram model led up to a 13% reduction in the perplexity compared with the baseline 3‐gram model. Morphological models decreased out‐of‐vocabulary word rate from 1.5% to 1.02%.