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Table 4: Comparative Performance with Earlier Re- sults on a Model-based Dataset.
"... In PAGE 6: ... Our results in Ta- ble 4 reiterate the closeness in performance of the incremen- tal window based alignment method to the highly optimized SW-PSSM alignment algorithm for the family, superfamily and fold level subsets. Table4 also shows results for the optimized local (local sequence alignment using a global scoring matrix), global 0 0.2 0.... In PAGE 6: ... Using sequence alignment techniques we would like to achieve these high levels of accu- racy. The results shown in Table4 for the various previously published schemes, as well as for our methods are the best achieved after optimization of the various parameters. We further analyze the data by annotating a model as being correct based on the LGscore value.... In PAGE 7: ...rror rates using the procedure described in Section 3.1.3. Though the SW-PSSM algorithm showed slightly better performance in terms of the overall alignment quality (Ta- ble 3 and Table4 ), it is interesting to note the window-based schemes using variable length a2 mers showed far better per- formance at the lower error rates. In particular before see- ing any incorrect predictions in the ranked aligned positions, the alignment methods using variable length a2 mers have a recall around 0.... ..."
Cited by 1
Table 4: Comparative Performance with Earlier Re- sults on a Model-based Dataset.
"... In PAGE 7: ... Our results in Ta- ble 4 reiterate the closeness in performance of the incremen- tal window based alignment method to the highly optimized SW-PSSM alignment algorithm for the family, superfamily and fold level subsets. Table4 also shows results for the optimized local (local sequence alignment using a global scoring matrix), global 0 0.2 0.... In PAGE 7: ... Using sequence alignment techniques we would like to achieve these high levels of accu- racy. The results shown in Table4 for the various previously published schemes, as well as for our methods are the best achieved after optimization of the various parameters. We further analyze the data by annotating a model as being correct based on the LGscore value.... In PAGE 8: ...rror rates using the procedure described in Section 3.1.3. Though the SW-PSSM algorithm showed slightly better performance in terms of the overall alignment quality (Ta- ble 3 and Table4 ), it is interesting to note the window-based schemes using variable length a2mers showed far better per- formance at the lower error rates. In particular before see- ing any incorrect predictions in the ranked aligned positions, the alignment methods using variable length a2mers have a recall around 0.... ..."
Cited by 1
Table 1: Model sequences of tile placements Models are based on (I) order of mention in the family history and (II) actual user sequence using technique A.
2004
"... In PAGE 7: ... Our results also demonstrate the advantages of employing a combination of techniques within the same dataset. For example, our application of technique A (model development) led to the development of a model that was almost identical to one based on order of mention ( Table1 ), which viewed in isolation might suggest that individual users complete the task to a similar degree and in similar ways. However, non-sequential analysis of the data revealed considerable variation in both degree and success of completion of the task (Table 4, Kennedy and Judd 2000) while sequence analysis demonstrated a substantial level of deviation of individual sequences from the order of mention model (Tables 2 and 3; Figure 1).... ..."
Cited by 1
Table 2: Evaluation results for the seven sequences of browsing histories analyzed building a single user model. In the rst column there are the results of the model based on the Vector Space Model along with the Relevance Feedback technique. The proposed ap- proach is evaluated in the second column.
2005
Cited by 3
Table 2. Activities Covered/Factors Explicitly Considered by Various Cost Models.2
2000
"... In PAGE 20: ...2.8 Summary of Model Based Techniques Table2 summarizes the parameters used and activities covered by the models discussed. Overall, model based techniques are good for budgeting, tradeoff analysis, planning and control, and investment analysis.... ..."
Cited by 15
Table 1: Model-based segmentation and visualization
"... In PAGE 8: ... As a simple example, colors and transparencies of such objects should be selected such that contrasts are easily perceived and all relevant objects are sufficiently visible. Comparison of Model-based Segmentation and Visualization In Table1 , we compare information used for model-based segmentation and visualization. Table 1: Model-based segmentation and visualization... ..."
Table 3. Performance of the model-based segmenter
2000
Cited by 25
Table 3. Performance of the model-based segmenter
2000
Cited by 25
Table 1: Evaluation results for the seven sequences of browsing histories individually analyzed. In the rst column there are the results of the model based on the Vector Space Model along with the Relevance Feed- back technique. The proposed approach without cues and the same approach with cues is evaluated in the second and third column. The table shows the aver- age of the evaluations assigned by an external person to the 25 keywords with the best score extracted from the user models. The evaluations range from 0 (worst) to 4 (best).
2005
"... In PAGE 9: ... We have run the recovery process two times: the rst with no probing cues, the second with a probing cue related to the current topic (usually taken from a query submitted by the users during the browsing). The results are shown in Table1 . It is possible to note how the proposed user model outperforms the traditional VSM approach only in some browsing ses- sions when no probing cue is employed.... ..."
Cited by 3
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