Multimedia content can be described in versatile ways as its essence is not limited to one view. For music data these multiple views could be a song’s audio features as well as its lyrics. Both of these modalities have their advantages as text may be easier to search in and could cover more of the ‘content semantics’ of a song, while omitting other types of semantic categorisation. (Psycho)acou...

Large unedited technical textual databases might contain information that cannot be properly extracted using Natural Language Processing (NLP) tools due to the many existent word errors. A good example is the MIMIC II database, where medical text reports are a direct representation of experts’ views on real time observable data. Such reports contain valuable information that can improve predict...

Textual concrete syntaxes for models are beneficial for many reasons. They foster usability and productivity because of their fast editing style, their usage of error markers, autocompletion and quick fixes. Furthermore, they can easily be integrated into existing tools such as diff/merge or information interchange through e-mail, wikis or blogs. Several frameworks and tools from different comm...

The divergence between the two textual variants of Dan 7:13 (“Old Greek” and “Theodotion”) and their distinct ways of understanding the relationship between Daniel’s “Ancient of Days” and “Son of Man” is insufficiently studied by scholars of the Book of Daniel, and is neglected by translators of the LXX. This article offers a critical examination of the status quaestionis and a discussion of th...

The availability of large geospatial data from different sources has dramatically increased, but for the usage of such data in geo-mashup or contextaware systems, a data fusion component is necessary. To solve the integration issue classifiers are obtained by supervised training, with feature vectors derived from textual and geospatial attributes. In an application example, a coherent part of G...

The ever growing number of textual historical collections calls for methods that can meaningfully connect and explore these. Different collections offer different perspectives, expressing views at the time of writing or even a subjective view of the author. We propose to connect heterogeneous digital collections through temporal references found in documents as well as their textual content. We...

我們所參與公開評測 NTCIR10 RITE-2[5]將文字蘊涵的研究分成兩種層面,首先是分兩 類(Binary Class, BC) ,任務的目標是單純判別 T1 與 T2 之間是否具有蘊涵關係。但句 子之間蘊涵關係並不能單純以有或沒有這麼簡單就區分開,NTCIR RITE 另外定義多類 (Multi Class, MC)這項任務,將句子之間的蘊涵分類為正向、雙向、矛盾、與獨立四種 關係。假設這個句子對具有蘊涵關係,但有可能兩個句子所包涵的資訊數量不同,造成 我們只能從其中一個句子推論出另一個句子的完整的意思,這樣的情況我們稱為兩個句 子間的蘊涵關係為正向蘊涵。反之兩個句子可以互相推論出另一個句子的含意,這樣的 情況我們就稱為雙向蘊涵關係。假設句子對之間沒有蘊涵關係,我們可以很合理認為兩 個句子所表達的意思不相同,但這並不完全正確的想法。可能兩個句子所包涵的資訊大 致相同只是少部份...

This paper describes the Recognizing Textual Entailment (RTE) system that our teams developed for TAC 2011. Our system combines the entailment score calculated by lexicallevel matching with the machine-learningbased filtering mechanism using various features obtained from lexical-level, chunk-level and predicate argument structure-level information. In the filtering mechanism, we try to discard...

This paper demonstrates the promise of augmenting interactive visualizations with semi-supervised machine learning techniques to improve the discovery of significant associations and insight in the search and analysis of textual information. More specifically, we have developed a system–called Gryffin–that hosts a unique collection of techniques that facilitate individualized investigative sear...