نتایج جستجو برای: textual enhancement
تعداد نتایج: 148407 فیلتر نتایج به سال:
This quasi-experimental study examined the effects of input-based, meaning-based output (MO) and traditional instruction (TI) on EFL learners’ grammar learning. To this end, 120 junior high school students were selected from 4 intact classes. Each class was assigned to an instructional condition, that is, textual enhancement (TE), input flood (IF), MO, and TI. Before the treatment, a multiple-c...
This study explored the effect of input vs. collaborative output tasks on Iranian EFL learners’ grammatical accuracy and their willingness to communicate (WTC). In so doing, the study utilized 3 input (i.e., textual enhancement, processing instruction, and discourse) and 3 collaborative output (i.e., dictogloss, reconstruction cloze task, and jigsaw) tasks and compared their effects on 5 Englis...
the investigation would certainly offer implications for translation, where the translators mostly adhere to only the ideational meaning of the sl text neglecting its textual meaning, a practice which mostly leads to target language texts which have lower readability(compared with their source language counterparts) due to their displaced thematization strategies.
Long’s Interactional Input Hypothesis and Smith’s Input Enhancement Hypothesis hold both foci on Zellig Harris's (1976) formalist approach. Accordingly, the pivotal role of learner’s attention as one of the subcomponents of focus-on-form approach may have confused instruction types. However, whether such learning theories on drawing learners' attention on target language forms suit all types of...
Contrast enhancement is one of the most important issues of image processing, pattern recognition and computer vision. The commonly used techniques for contrast enhancement fall into two categories: (1) indirect methods of contrast enhancement and (2) direct methods of contrast enhancement. Indirect approaches mainly modify histogram by assigning new values to the original intensity levels. His...
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...
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