Articles

In this paper, we probe the problem of organi- zation name disambiguation on twitter mes- sages. This task is challenging due to the fact of lacking sufficient information in a tweet message. Instead of conventional methods based on mining external information from web sources to enrich information about or- ganization, …...

This paper proposes a keyword extraction process, based on the PageRank algorithm, to reduce noise of input data for measur- ing semantic similarity. This paper will in- troduce several features related to imple- mentation and discuss their effects. It will also discuss experimental results which showed significantly improved document retrieval …...

People are generating more and more short texts. There is an urgent demand to classify short texts into different domains. Due to the shortness and sparseness of short texts, con- ventional methods based on Vector Space Model (VSM) have limitations. To tackle the data scarcity problem, we propose a new …...

In this paper, we describe a Turkish factoid QA system which uses surface level patterns called answer patterns in order to extract the answers from the documents that are retrieved from the web. The answer patterns are learned using five different answer pattern extraction methods with the help of the …...

Mining compound words and their pro- nunciations is essential for Japanese in- put method editors (IMEs). We propose to use a chunk-based dependency parser to mine new words, collocations and predicate-argument phrases from large- scale Japanese Web pages and tweets. The pronunciations of the compound words are automatically rewritten by …...

We address the task of improving the qual- ity of lexicon bootstrapping, i.e., of ex- panding a semantic lexicon on a given cor- pus. A main problem of iterative boot- strapping techniques is the fact that lex- icon quality degrades gradually as more and more false terms are added. We …...

In this paper, we present and compare various centrality measures for graph- based keyphrase extraction. Through ex- periments carried out on three standard datasets of different languages and do- mains, we show that simple degree cen- trality achieve results comparable to the widely used TextRank algorithm, and that closeness centrality …...

In this paper, we present a translation template model to translate Chinese unknown words. The model exploits translation templates, which are extracted automatically from a word-aligned parallel corpus, to translate unknown words. The translation templates are designed in accordance with the structure of unknown words. When an unknown word is …...

Named entity recognition in queries is the task of identifying sequences of terms in search queries that refer to a unique con- cept. This problem is catching increas- ing attention, since the lack of context in short queries makes this task difficult for full-text off-the-shelf named entity recog- nizers. In …...

Given the relatively small amount of work on event coreference resolution, our under- standing of the task is arguably fairly lim- ited. This makes it difficult to determine how to improve an event coreference re- solver. We seek to gain a better under- standing of the state of the art …...

In this paper we present our work on adapting a state-of-the-art anaphora res- olution system for a resource poor lan- guage, namely Bengali. Performance of any anaphoric resolver greatly depends on the quality of a high accurate mention de- tector. We develop a number of mod- els for mention detection …...

This paper addresses the open prob- lem of mathematical term sense disam- biguation. We introduce a method that uses a MathML parallel markup corpus to generate relevant training and testing datasets. Based on the dataset generated, we use Support Vector Machine classifier to disambiguate the sense of mathematical terms. Experimental …...

This paper attempts to identify the impor- tance of sentiment words in financial re- ports on financial risk. By using a finance- specific sentiment lexicon, we apply re- gression and ranking techniques to ana- lyze the relations between sentiment words and financial risk. The experimental re- sults show that, based …...

Chinese time entity is quite complex. In this paper, we give a comprehensive lin- guistic study on it. Based on the analy- sis, we present a rule system which on- ly considers the inner structure of Chinese time entities for the recognition. Exper- iments on Sinica and TempEval-2 corpus show …...

Natural language generation systems rely on taxonomic thesauri for tasks such as lexical choice and aggregation. WordNet is one such taxonomy, but it is limited in size. Motivated by the needs of a genera- tion system in the scientific literature do- main, we present a method for building a taxonomic …...

Semantic Role Labeling (SRL) is an im- portant task since it benefits a wide range of natural language processing applica- tions. Given a sentence, the task of SRL is to identify arguments for a pred- icate (target verb or noun) and assign semantically meaningful labels to them. Dependency parsing based …...

This paper is concerned with the prob- lem of automatic essay grading, where the task is to grade student written essays given course materials and a set of human- graded essays as training data. Latent Se- mantic Analysis (LSA) has been used ex- tensively over the years to accomplish this …...

The metalinguistic facilities of natural lan- guage are crucial to our ability to communi- cate, but the patterns behind the appearance of metalanguage—and thus the clues for how we may instruct computers to detect it—have re- mained relatively unknown. This paper de- scribes the first results on the feasibility of …...

This work aims at constructing a corpus to satisfy such requirements to support re- search towards professional writing assis- tance. Our corpus is a collection of sci- entific work written by non-native speak- ers that has been proofread by native En- glish experts. A new annotation scheme, which is based …...

Ubuntu’s Internet Relay Chat technical support channel has bots that output specific messages in response to com- mand words from other channel users. These messages can be used to answer frequently-asked questions instead of re- quiring an expert to (repeatedly) type a lengthy reply. We describe an approach to automatically …...