Browsing by Author "Muntaha Iqbal"

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    Developing an Urdu Lemmatize
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2017) Muntaha Iqbal; FA15-RCS-010; LHR TP 6821
    Lemmatization is a process of obtaining root form of a given word. Lemmatizer is an important part of Natural Language Processing (NLP) toolkit and is essential for many NLP systems e.g. Information Retrieval (IR), plagiarism and text reuse detection, Information Extraction (IE), Machine Translation (MT), Word Sense Disambiguation (WSD) etc. Urdu is a widely spoken language in the world, but very less work has been done on developing basic NLP tools for this language, one of them is Urdu lemmatizer. Since Urdu is a morphologically rich language and has words with many inflectional and derivational forms, development of an efficient lemmatizer is a challenging task and it will be useful for many Urdu NLP applications. This research work aims to develop an efficient lemmatizer for Urdu language. For this purpose, we explored two main approaches: (1) dictionary lookup approach and (2) rule based approach. Note that we also tried combinations of these two approaches. For the first approach, we build a large dictionary of 131,539 entries. In this dictionary, 3,026 are exceptional words, 22,181 are multi-word expression, and 18,267 are Named Entities (NEs) for person and 79,418 are Named Entities (NEs) for locations. Remaining 8,647 are variants of most frequent 5,000 Urdu language words. For the second approach, we extracted a total of 215 rules (67 are prefix, 128 are postfixes) from raw Urdu text. We also developed a benchmark test dataset of 1,000 Urdu words to evaluate our proposed approaches for Urdu lemmatization task. The proposed lemmatizer was evaluated using six different approaches: (1) Dictionary Lookup Approach (DLA), (2) Rule Based Approach (RBA), (3) Dictionary (DIC) + Exceptional Word List (EWL) Approach, (4) Rule Based + Exceptional Word List Approach, (5) Rule Based + Final Dictionary Approach and (6) Final Dictionary + Rule Based Approach. Evaluation was carried out using Accuracy measure. Results showed that Dictionary + Rule Based Approach gave highest Accuracy of 82.9%. We also developed a prototype system, which takes an Urdu word as input and outputs its lemma
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    Lancer
    (Library Information Services, CUI Lahore, 2021) S.M.Haseeb Iqbal; SP19-BCS-042; Muntaha Iqbal
    Freelancing platforms are at a rise nowadays, people can hire or get hired directly from their homes. However, freelancers and people, hiring them, have to face issues like high project commissions, error-prone communication methods, multiple employee management issues, very slow rank up of freelancers and inaccessible payment methods. However, Lancer solves the problem, it is a Free-Lancing marketplace that will provide users with some unique facilities. Such as team building mode which will allow the buyer to hire experts from different fields and conjoin them in a team, making the whole process a lot faster, users will experience interaction like never seen before with the help of audio, video calling, and group chat, spam protection will help make the environment safer and spam-proof. Experienced freelancers joining the platform will have the opportunity of upgrading their level by giving speci