A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts

Date

2016-09-08

Author

Kama, Batuhan
ÖZTÜRK, MURAT
Karagöz, Pınar
Toroslu, İsmail Hakkı
Ozay, Ozcan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

223
views

0
downloads

In this article, a new unsupervised feature extraction method for aspect-based sentiment analysis is proposed. This method improves the performance of frequency based feature extraction by using an online search engine. Although frequency based feature extraction methods produce good precision and recall values on formal texts, they are not very successful on informal texts. Our proposed algorithm takes the features of items suggested by frequency based feature extraction methods, then, eliminates the features which do not co-occur with the item, whose features are sought, on the Web. Since the proposed method constructs the candidate feature set of the item from the Web, it is domain-independent. The results of experiments reveal that for informal Turkish texts, much higher performance than frequency based method is achieved.

Subject Keywords

Computer Science, Artificial Intelligence, Computer Science, Information Systems, Computer Science, Theory & Methods

URI

https://hdl.handle.net/11511/47860

DOI

https://doi.org/10.1007/978-3-319-43946-4_15

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Fusion of Image Segmentations under Markov Random Fields Karadag, Ozge Oztimur; Yarman Vural, Fatoş Tunay (2014-08-28) In this study, a fast and efficient consensus segmentation method is proposed which fuses a set of baseline segmentation maps under an unsupervised Markov Random Fields (MRF) framework. The degree of consensus among the segmentation maps are estimated as the relative frequency of co-occurrences among the adjacent segments. Then, these relative frequencies are used to construct the energy function of an unsupervised MRF model. It is well-known that MRF framework is commonly used for formulating the spatial r...
Semantic information-based alternative plan generation for multiple query optimization Polat, Faruk; Alhajj, R (Elsevier BV, 2001-09-01) This paper addresses the impact of semantic information about queries on alternative plan generation (APG) for multiple query optimization (MQO). MQO covers optimizing the execution of a set of queries together where each query in the set to be optimized has several alternative execution plans. A multiple query optimizer selects an alternative plan for each query to obtain an optimal global execution plan. Our approach uses information such as common relations, common possible joins and common conditions to...
Structural and event based multimodal video data modeling Oztarak, Hakan; Yazıcı, Adnan (2006-01-01) In this paper, a structural and event based multimodal video data model (SEBM) is proposed. SEBM supports three different modalities that are visual, auditory and textual modalities for video database systems and it can dissolve these three modalities within a single structure. This dissolving procedure is a mimic of human interpretation regarding video data. The SEBM video data model is used to answer content-based, spatio-temporal and fuzzy queries about video data. A SEBM prototype system is developed to...
A new reactive method for processing web usage data Bayır, Murat Ali; Toroslu, İsmail Hakkı; Department of Computer Engineering (2006) In this thesis, a new reactive session reconstruction method 'Smart-SRA' is introduced. Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigations of Web users. As in classical data mining, data processing and pattern discovery are the main issues in web usage mining. The first phase of the web usage mining is the data processing phase including session reconstruction. Session reconstruction is the most important task of web usage mining...
A window-based time series feature extraction method Katircioglu-Ozturk, Deniz; GÜVENİR, H. ALTAY; Ravens, Ursula; Baykal, Nazife (2017-10-01) This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publi...

Citation Formats

B. Kama, M. ÖZTÜRK, P. Karagöz, İ. H. Toroslu, and O. Ozay, “A Web Search Enhanced Feature Extraction Method for Aspect-Based Sentiment Analysis for Turkish Informal Texts,” 2016, vol. 9829, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/47860.