The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Research in opinion analysis have drawn a great attention these days. Many of the effective opinion analysis system are based on supervised learning technology. However there lack of annotation sentiment corpora for Chinese opinion analysis. The purpose of our work is try to make use of annotation English corpora, where are rich and reliable to improve opinion analysis in Chinese. We propose a approach...
Considering of the features' distribution but not just the counts of features' appearances in sequence makes exponential language models more powerful to capture the global language phenomena. This paper constructs an exponential language model with binary variables' distributions of features, and uses minimum sample risk training method to train model by utilizing more features and adjusting their...
In this paper, we present a new method to extract product entity from Chinese customer reviews. The approach requires no segmentation, no domain dictionary and little prior domain knowledge, which is more suitable for domain with resource-limited. Quite different from the previous work, the proposed method first get the entity candidates use a general version bootstrapping algorithm and then distribute...
This paper presents a novel application of incorporating Alternating Structure Optimization (ASO) to conduct the task of text chunking of Semantic Role Labeling (SRL) in Chinese texts. ASO is a competent linear algorithm based on the theory of multi-task learning. In this paper, by constructing several SRL tasks to constitute a multi-task, we are able to encode the inference obtained by ASO algorithm...
This paper presents an exponential language model (ELM) for modeling and managing knowledge elements. The model has been developed based on minimum sample risk (MSR) algorithm, which is a discriminative training method. ELM uses features to capture global, domain, or sentential language phenomena that is composed of name entities, part of speech strings, personal usage words, positions of words, sentence...
This paper proposes an novel approach to annotate function tags for unparsed text. What distinguishes our work from other attempts in such task is that we assign function tags directly basing on lexical information other than on parsed trees. In order to demonstrate the effectiveness and versatility of our method, we investigate two statistical models for automatic annotation, one is log-linear maximum...
Chinese Pinyin-to-character conversion is a key technology in Chinese Pinyin input system. In sentence based Pinyin-to-character conversion, segmentation of Pinyin string has important influence on performance of Pinyin-to-character conversion. There are lots of ambiguities in segmentation of Pinyin string. This paper classifies them into overlap and combinational ambiguities, and proposes disambiguation...
Recent years have seen great process in studying English question classification. In our research, we learn Chinese question classification by exploiting the result of lexical, syntactic and semantic parsing on question sentences. Support vector machines are adopted to train a classifier on 6 coarse categories using single and combination of different parsing results as features. We find that even...
Chinese named entity recognition (NER) is studied in two directions: inner structure and outer surroundings. Inner structural analyses induce constitutions of person, location and organization name from the point of linguistics. However inner structural rules for named entities only provide necessary conditions for a sequence of Chinese characters being an entity name but not sufficient. Whether a...
Since noun phrases are the most popular phrases in texts, noun phrase identification is one of vital subtasks of natural language processing. Generally Chinese noun phrases have hierarchical inner structures. This paper proposes an approach of defining various levels of granularity for noun phrases, catering for different application demands. Three levels of granularity noun phrases are proposed,...
This paper uses the adaptive boosting (AdaBoosting) algorithm to the task of word sense disambiguation (WSD) for Chinese verbs. The AdaBoosting algorithm is a kind of ensemble learning method used for classification. We have implemented the classifier using a feature set combining collocation features, syntactic features and semantic features. We test the model on eight polysemous verbs in Chinese...
We have built a semantic role labeling (SRL) system for Chinese clauses, with some desired information of the main-predicate in each clause and the relevant functional slots. The ability of our SRL system dealing with simple clauses is considered as the basic performance of the system. When processing more complex clauses (namely clauses with more than one verb phrase in our definition of complex...
Entity relation extraction (RE) is an very important research domain in information extraction, we can regard RE as a classification problem in this paper, RE is still original study field in Chinese language now, maximum entropy (ME)-based machine learning is the first time to be used to extract entity relations between named entities from Chinese texts, Thirteen features have been designed for entity...
In the task of Chinese word segmentation, there are two main segmentation ambiguities, overlapping ambiguity and combination ambiguity. The paper analyzes properties of ambiguities and supposes multi-knowledge approach to disambiguate. Multi-knowledge refers to the knowledge from statistic of large corpus and syntactic, semantic or discourse information about ambiguous words. Class based N-gram and...
A specific prototype information service system was proposed by this paper, which can send interesting information to user with database search way from unstructured text. In order to achieve this goal, two fundamental issues were studied by using maximum entropy (ME) algorithm, which is named entity recognition and relation extraction. Our named entity recognition approach is distinguished from most...
In Chinese word segmentation task, combination ambiguity is one of challenges not being well settled. The main obstacle exists in the detection of ambiguous words in given texts and their proper segmentations. This paper puts forward a practical approach to automatically collecting ambiguous words and disambiguating based on maximum entropy principle. The experimental result reveals the approach of...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.